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+<!-- Changed by: Agnes Lievre, 12-Oct-2000 -->\r
+</head>\r
+\r
+<body bgcolor="#FFFFFF" link="#0000FF" vlink="#0000FF" lang="FR"\r
+style="tab-interval:35.4pt">\r
+\r
+<hr size="3" noshade color="#EC5E5E">\r
+\r
+<h1 align="center" style="text-align:center"><span lang="EN-GB" style="color:#00006A;\r
+mso-ansi-language:EN-GB">Computing Health\r
+Expectancies using IMaCh</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h1>\r
+\r
+<h1 align="center" style="text-align:center"><span lang="EN-GB" style="font-size:\r
+18.0pt;color:#00006A;mso-ansi-language:EN-GB">(a Maximum\r
+Likelihood Computer Program using Interpolation of Markov Chains)</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h1>\r
+\r
+<p align="center" style="text-align:center"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB"> <o:p></o:p></span></p>\r
+\r
+<p align="center" style="text-align:center"><a\r
+href="http://www.ined.fr/"><span style="text-decoration:none;text-underline:none"><img src="logo-ined.gif" border="0"\r
+width="151" height="76" id="_x0000_i1026"></span></a><img\r
+src="euroreves2.gif" width="151" height="75" id="_x0000_i1027"></p>\r
+\r
+<h3 align="center" style="text-align:center"><a\r
+href="http://www.ined.fr/"><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB">INED</span><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB"></a> and </span><a\r
+href="http://euroreves.ined.fr"><span lang="EN-GB" style="color:#00006A;\r
+mso-ansi-language:EN-GB">EUROREVES</span><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB"><o:p></o:p></span></a></h3>\r
+\r
+<p align="center" style="text-align:center"><strong><span lang="EN-GB" style="font-size:13.5pt;color:#00006A;mso-ansi-language:EN-GB">Version 0.7,\r
+February 2002</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></strong></p>\r
+\r
+<hr size="3" noshade color="#EC5E5E">\r
+\r
+<p align="center" style="text-align:center"><strong><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB">Authors of\r
+the program: </span></strong><a href="http://sauvy.ined.fr/brouard"><strong><span lang="EN-GB" style="color:#00006A;\r
+mso-ansi-language:EN-GB">Nicolas\r
+Brouard</span><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB"></strong></a><strong>, senior researcher at the </span></strong><a\r
+href="http://www.ined.fr"><strong><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB">Institut National d'Etudes\r
+Démographiques</span><span lang="EN-GB" style="color:#00006A;\r
+mso-ansi-language:EN-GB"></strong></a><strong> (INED, Paris) in the\r
+"Mortality, Health and Epidemiology" Research Unit </span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></strong></p>\r
+\r
+<p align="center" style="text-align:center"><strong><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB">and Agnès\r
+Lièvre</span></strong><b><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB"><br clear="left"\r
+style="mso-special-character:line-break">\r
+</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></b></p>\r
+\r
+<h4><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB">Contribution to the mathematics: C. R. Heathcote </span><span lang="EN-GB" style="font-size:\r
+10.0pt;color:#00006A;mso-ansi-language:EN-GB">(Australian\r
+National University, Canberra).</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h4>\r
+\r
+<h4><span style="color:#00006A">Contact: Agnès Lièvre (</span><a href="mailto:lievre@ined.fr"><i><span style="color:#00006A">lievre@ined.fr</span><span style="color:#00006A"></i></a>)\r
+</span></h4>\r
+\r
+<hr>\r
+<span style="font-size:12.0pt;font-family:"Times New Roman";mso-fareast-font-family:\r
+"Times New Roman";mso-ansi-language:FR;mso-fareast-language:FR;mso-bidi-language:\r
+AR-SA">\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l17 level1 lfo3;tab-stops:list 36.0pt"><a\r
+ href="#intro"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Introduction</span><span style="mso-ansi-language:EN-GB"></a> <span lang="EN-GB"><o:p></o:p></span></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l17 level1 lfo3;tab-stops:list 36.0pt"><a\r
+ href="#data"><span lang="EN-GB" style="mso-ansi-language:EN-GB">On what kind of data can it be used?</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l17 level1 lfo3;tab-stops:list 36.0pt"><a\r
+ href="#datafile"><span lang="EN-GB" style="mso-ansi-language:EN-GB">The data file</span><span style="mso-ansi-language:EN-GB"></a> <span lang="EN-GB"><o:p></o:p></span></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l17 level1 lfo3;tab-stops:list 36.0pt"><a\r
+ href="#biaspar"><span lang="EN-GB" style="mso-ansi-language:EN-GB">The parameter file</span><span style="mso-ansi-language:EN-GB"></a> <span lang="EN-GB"><o:p></o:p></span></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l17 level1 lfo3;tab-stops:list 36.0pt"><a\r
+ href="#running"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Running Imach</span><span style="mso-ansi-language:EN-GB"></a> <span lang="EN-GB"><o:p></o:p></span></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l17 level1 lfo3;tab-stops:list 36.0pt"><a\r
+ href="#output"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Output files and graphs</span><span style="mso-ansi-language:EN-GB"></a> <span lang="EN-GB"><o:p></o:p></span></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l17 level1 lfo3;tab-stops:list 36.0pt"><a\r
+ href="#example">Exemple</a> </li>\r
+</ul>\r
+</span>\r
+<hr>\r
+\r
+<h2><a name="intro"><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB">Introduction</span><span style="mso-bookmark:intro"></span><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB"><o:p></o:p></span></a></h2>\r
+\r
+<p style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">This program computes <b>Healthy\r
+Life Expectancies</b> from <b>cross-longitudinal data</b> using\r
+the methodology pioneered by Laditka and Wolf (1). Within the\r
+family of Health Expectancies (HE), Disability-free life\r
+expectancy (DFLE) is probably the most important index to\r
+monitor. In low mortality countries, there is a fear that when\r
+mortality declines, the increase in DFLE is not proportionate to\r
+the increase in total Life expectancy. This case is called the <em>Expansion\r
+of morbidity</em>. Most of the data collected today, in\r
+particular by the international </span><a href="http://euroreves/reves"><span lang="EN-GB" style="mso-ansi-language:EN-GB">REVES</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a>\r
+network on Health expectancy, and most HE indices based on these\r
+data, are <em>cross-sectional</em>. It means that the information\r
+collected comes from a single cross-sectional survey: people from\r
+various ages (but mostly old people) are surveyed on their health\r
+status at a single date. Proportion of people disabled at each\r
+age, can then be measured at that date. This age-specific\r
+prevalence curve is then used to distinguish, within the\r
+stationary population (which, by definition, is the life table\r
+estimated from the vital statistics on mortality at the same\r
+date), the disable population from the disability-free\r
+population. Life expectancy (LE) (or total population divided by\r
+the yearly number of births or deaths of this stationary\r
+population) is then decomposed into DFLE and DLE. This method of\r
+computing HE is usually called the Sullivan method (from the name\r
+of the author who first described it).<o:p></o:p></span></p>\r
+\r
+<p style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Age-specific proportions of people\r
+disable are very difficult to forecast because each proportion\r
+corresponds to historical conditions of the cohort and it is the\r
+result of the historical flows from entering disability and\r
+recovering in the past until today. The age-specific intensities\r
+(or incidence rates) of entering disability or recovering a good\r
+health, are reflecting actual conditions and therefore can be\r
+used at each age to forecast the future of this cohort. For\r
+example if a country is improving its technology of prosthesis,\r
+the incidence of recovering the ability to walk will be higher at\r
+each (old) age, but the prevalence of disability will only\r
+slightly reflect an improve because the prevalence is mostly\r
+affected by the history of the cohort and not by recent period\r
+effects. To measure the period improvement we have to simulate\r
+the future of a cohort of new-borns entering or leaving at each\r
+age the disability state or dying according to the incidence\r
+rates measured today on different cohorts. The proportion of\r
+people disabled at each age in this simulated cohort will be much\r
+lower (using the example of an improvement) that the proportions\r
+observed at each age in a cross-sectional survey. This new\r
+prevalence curve introduced in a life table will give a much more\r
+actual and realistic HE level than the Sullivan method which\r
+mostly measured the History of health conditions in this country.<o:p></o:p></span></p>\r
+\r
+<p style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Therefore, the main question is how\r
+to measure incidence rates from cross-longitudinal surveys? This\r
+is the goal of the IMaCH program. From your data and using IMaCH\r
+you can estimate period HE and not only Sullivan's HE. Also the\r
+standard errors of the HE are computed.<o:p></o:p></span></p>\r
+\r
+<p style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">A cross-longitudinal survey\r
+consists in a first survey ("cross") where individuals\r
+from different ages are interviewed on their health status or\r
+degree of disability. At least a second wave of interviews\r
+("longitudinal") should measure each new individual\r
+health status. Health expectancies are computed from the\r
+transitions observed between waves and are computed for each\r
+degree of severity of disability (number of life states). More\r
+degrees you consider, more time is necessary to reach the Maximum\r
+Likelihood of the parameters involved in the model. Considering\r
+only two states of disability (disable and healthy) is generally\r
+enough but the computer program works also with more health\r
+statuses.<span style="mso-spacerun:\r
+yes"> </span><br>\r
+<br>\r
+The simplest model is the multinomial logistic model where <i>pij</i>\r
+is the probability to be observed in state <i>j</i> at the second\r
+wave conditional to be observed in state <em>i</em> at the first\r
+wave. Therefore a simple model is: log<em>(pij/pii)= aij +\r
+bij*age+ cij*sex,</em> where '<i>age</i>' is age and '<i>sex</i>'\r
+is a covariate. The advantage that this computer program claims,\r
+comes from that if the delay between waves is not identical for\r
+each individual, or if some individual missed an interview, the\r
+information is not rounded or lost, but taken into account using\r
+an interpolation or extrapolation. <i>hPijx</i> is the\r
+probability to be observed in state <i>i</i> at age <i>x+h</i>\r
+conditional to the observed state <i>i</i> at age <i>x</i>. The\r
+delay '<i>h</i>' can be split into an exact number (<i>nh*stepm</i>)\r
+of unobserved intermediate states. This elementary transition (by\r
+month or quarter trimester, semester or year) is modeled as a\r
+multinomial logistic. The <i>hPx</i> matrix is simply the matrix\r
+product of <i>nh*stepm</i> elementary matrices and the\r
+contribution of each individual to the likelihood is simply <i>hPijx</i>.\r
+<o:p></o:p></span></p>\r
+\r
+<p style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">The program presented in this\r
+manual is a quite general program named <strong>IMaCh</strong>\r
+(for <strong>I</strong>nterpolated <strong>MA</strong>rkov <strong>CH</strong>ain),\r
+designed to analyse transition data from longitudinal surveys.\r
+The first step is the parameters estimation of a transition\r
+probabilities model between an initial status and a final status.\r
+From there, the computer program produces some indicators such as\r
+observed and stationary prevalence, life expectancies and their\r
+variances and graphs. Our transition model consists in absorbing\r
+and non-absorbing states with the possibility of return across\r
+the non-absorbing states. The main advantage of this package,\r
+compared to other programs for the analysis of transition data\r
+(For example: Proc Catmod of SAS<sup>(r)</sup>) is that the whole\r
+individual information is used even if an interview is missing, a\r
+status or a date is unknown or when the delay between waves is\r
+not identical for each individual. The program can be executed\r
+according to parameters: selection of a sub-sample, number of\r
+absorbing and non-absorbing states, number of waves taken in\r
+account (the user inputs the first and the last interview), a\r
+tolerance level for the maximization function, the periodicity of\r
+the transitions (we can compute annual, quarterly or monthly\r
+transitions), covariates in the model. It works on Windows or on\r
+Unix.<o:p></o:p></span></p>\r
+\r
+<hr>\r
+\r
+<p><span lang="EN-GB" style="mso-ansi-language:EN-GB">(1) Laditka, Sarah B. and Wolf, Douglas A. (1998), "New\r
+Methods for Analyzing Active Life Expectancy". <i>Journal of\r
+Aging and Health</i>. </span>Vol 10, No. 2. </p>\r
+\r
+<hr>\r
+\r
+<h2><a name="data"><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB">On what kind of data can it be used?</span><span style="mso-bookmark:data"></span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h2>\r
+\r
+<p style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">The minimum data required for a\r
+transition model is the recording of a set of individuals\r
+interviewed at a first date and interviewed again at least one\r
+another time. From the observations of an individual, we obtain a\r
+follow-up over time of the occurrence of a specific event. In\r
+this documentation, the event is related to health status at\r
+older ages, but the program can be applied on a lot of\r
+longitudinal studies in different contexts. To build the data\r
+file explained into the next section, you must have the month and\r
+year of each interview and the corresponding health status. But\r
+in order to get age, date of birth (month and year) is required\r
+(missing values is allowed for month). Date of death (month and\r
+year) is an important information also required if the individual\r
+is dead. Shorter steps (i.e. a month) will more closely take into\r
+account the survival time after the last interview.<o:p></o:p></span></p>\r
+\r
+<hr>\r
+\r
+<h2><a name="datafile"><span lang="EN-GB" style="color:#00006A;mso-ansi-language:\r
+EN-GB">The data file</span><span style="mso-bookmark:datafile"></span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h2>\r
+\r
+<p style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">In this example, 8,000 people have\r
+been interviewed in a cross-longitudinal survey of 4 waves (1984,\r
+1986, 1988, 1990). Some people missed 1, 2 or 3 interviews.\r
+Health statuses are healthy (1) and disable (2). The survey is\r
+not a real one. It is a simulation of the American Longitudinal\r
+Survey on Aging. The disability state is defined if the\r
+individual missed one of four ADL (Activity of daily living, like\r
+bathing, eating, walking). Therefore, even is the individuals\r
+interviewed in the sample are virtual, the information brought\r
+with this sample is close to the situation of the United States.\r
+Sex is not recorded is this sample.<o:p></o:p></span></p>\r
+\r
+<p><span lang="EN-GB" style="mso-ansi-language:EN-GB">Each line of the data set (named </span><a href="data1.txt"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">data1.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a>\r
+in this first example) is an individual record which fields are: <o:p></o:p></span></p>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">Index\r
+ number</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>: positive number (field 1) <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">First\r
+ covariate</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b> positive number (field 2) <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">Second\r
+ covariate</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b> positive number (field 3) <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><a\r
+ name="Weight"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">Weight</span><span style="mso-bookmark:Weight"></span><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB"></b></a>: positive number (field\r
+ 4) . In most surveys individuals are weighted according\r
+ to the stratification of the sample.<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">Date\r
+ of birth</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>: coded as mm/yyyy. Missing dates are coded\r
+ as 99/9999 (field 5) <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">Date\r
+ of death</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>: coded as mm/yyyy. Missing dates are coded\r
+ as 99/9999 (field 6) <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">Date\r
+ of first interview</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>: coded as mm/yyyy. Missing dates\r
+ are coded as 99/9999 (field 7) <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">Status\r
+ at first interview</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>: positive number. Missing values\r
+ ar coded -1. (field 8) <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">Date\r
+ of second interview</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>: coded as mm/yyyy. Missing dates\r
+ are coded as 99/9999 (field 9) <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><strong><span lang="EN-GB" style="mso-ansi-language:EN-GB">Status\r
+ at second interview</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></strong> positive number. Missing\r
+ values ar coded -1. (field 10) <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">Date\r
+ of third interview</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>: coded as mm/yyyy. Missing dates\r
+ are coded as 99/9999 (field 11) <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><strong><span lang="EN-GB" style="mso-ansi-language:EN-GB">Status\r
+ at third interview</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></strong> positive number. Missing\r
+ values ar coded -1. (field 12) <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">Date\r
+ of fourth interview</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>: coded as mm/yyyy. Missing dates\r
+ are coded as 99/9999 (field 13) <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><strong><span lang="EN-GB" style="mso-ansi-language:EN-GB">Status\r
+ at fourth interview</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></strong> positive number. Missing\r
+ values are coded -1. (field 14) <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l12 level1 lfo6;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">etc<o:p></o:p></span></li>\r
+</ul>\r
+\r
+<p><span lang="EN-GB" style="mso-ansi-language:EN-GB"> <o:p></o:p></span></p>\r
+\r
+<p style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">If your longitudinal survey do not\r
+include information about weights or covariates, you must fill\r
+the column with a number (e.g. 1) because a missing field is not\r
+allowed.<o:p></o:p></span></p>\r
+\r
+<hr>\r
+\r
+<h2><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB">Your first example parameter file</span><a\r
+href="http://euroreves.ined.fr/imach"></a><a name="uio"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h2>\r
+\r
+<h2><a name="biaspar"><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a>#Imach version 0.7, February 2002,\r
+INED-EUROREVES <o:p></o:p></span></h2>\r
+\r
+<p><span lang="EN-GB" style="mso-ansi-language:EN-GB">This is a comment. Comments start with a '#'.<o:p></o:p></span></p>\r
+\r
+<h4><span lang="EN-GB" style="color:red;mso-ansi-language:EN-GB">First uncommented line</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h4>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">title=1st_example datafile=data1.txt lastobs=8600 firstpass=1 lastpass=4<o:p></o:p></span></pre>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l1 level1 lfo9;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">title=</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ 1st_example is title of the run. <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l1 level1 lfo9;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">datafile=</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>data1.txt\r
+ is the name of the data set. Our example is a six years\r
+ follow-up survey. It consists in a baseline followed by 3\r
+ reinterviews. <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l1 level1 lfo9;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">lastobs=</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ 8600 the program is able to run on a subsample where the\r
+ last observation number is lastobs. It can be set a\r
+ bigger number than the real number of observations (e.g.\r
+ 100000). In this example, maximisation will be done on\r
+ the 8600 first records. <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l1 level1 lfo9;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">firstpass=1</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ , <b>lastpass=4 </b>In case of more than two interviews\r
+ in the survey, the program can be run on selected\r
+ transitions periods. firstpass=1 means the first\r
+ interview included in the calculation is the baseline\r
+ survey. lastpass=4 means that the information brought by\r
+ the 4th interview is taken into account.<o:p></o:p></span></li>\r
+</ul>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB"> <o:p></o:p></span></p>\r
+\r
+<h4\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="color:red;mso-ansi-language:EN-GB">Second\r
+uncommented line</span><a name="biaspar-2"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h4>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">ftol=1.e-08 stepm=1 ncov=2 nlstate=2 ndeath=1 maxwav=4 mle=1 weight=0<o:p></o:p></span></pre>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l14 level1 lfo12;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">ftol=1e-8</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ Convergence tolerance on the function value in the\r
+ maximisation of the likelihood. Choosing a correct value\r
+ for ftol is difficult. 1e-8 is a correct value for a 32\r
+ bits computer.<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l14 level1 lfo12;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">stepm=1</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ Time unit in months for interpolation. Examples:<o:p></o:p></span></li>\r
+ <li><ul type="circle">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:\r
+ auto;text-align:justify;mso-list:l14 level2 lfo12;tab-stops:list 72.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">If\r
+ stepm=1, the unit is a month <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:\r
+ auto;text-align:justify;mso-list:l14 level2 lfo12;tab-stops:list 72.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">If\r
+ stepm=4, the unit is a trimester<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:\r
+ auto;text-align:justify;mso-list:l14 level2 lfo12;tab-stops:list 72.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">If\r
+ stepm=12, the unit is a year <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:\r
+ auto;text-align:justify;mso-list:l14 level2 lfo12;tab-stops:list 72.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">If\r
+ stepm=24, the unit is two years<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:\r
+ auto;text-align:justify;mso-list:l14 level2 lfo12;tab-stops:list 72.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">...\r
+<o:p></o:p></span> </li>\r
+ </ul>\r
+ </li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l14 level1 lfo12;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">ncov=2</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ Number of covariates in the datafile. The intercept and\r
+ the age parameter are counting for 2 covariates.<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l14 level1 lfo12;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">nlstate=2</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ Number of non-absorbing (alive) states. Here we have two\r
+ alive states: disability-free is coded 1 and disability\r
+ is coded 2. <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l14 level1 lfo12;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">ndeath=1</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ Number of absorbing states. The absorbing state death is\r
+ coded 3. <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l14 level1 lfo12;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">maxwav=4</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ Number of waves in the datafile.<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l14 level1 lfo12;tab-stops:list 36.0pt"><a\r
+ name="mle"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">mle</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b></a><b>=1</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b> Option for the\r
+ Maximisation Likelihood Estimation. <o:p></o:p></span></li>\r
+ <li><ul type="circle">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:\r
+ auto;text-align:justify;mso-list:l14 level2 lfo12;tab-stops:list 72.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">If\r
+ mle=1 the program does the maximisation and the\r
+ calculation of health expectancies <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:\r
+ auto;text-align:justify;mso-list:l14 level2 lfo12;tab-stops:list 72.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">If\r
+ mle=0 the program only does the calculation of\r
+ the health expectancies. <o:p></o:p></span></li>\r
+ </ul>\r
+ </li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l14 level1 lfo12;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">weight=0</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ Possibility to add weights. <o:p></o:p></span></li>\r
+ <li><ul type="circle">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:\r
+ auto;text-align:justify;mso-list:l14 level2 lfo12;tab-stops:list 72.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">If\r
+ weight=0 no weights are included <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:\r
+ auto;text-align:justify;mso-list:l14 level2 lfo12;tab-stops:list 72.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">If\r
+ weight=1 the maximisation integrates the weights\r
+ which are in field </span><a href="#Weight"><span lang="EN-GB" style="mso-ansi-language:EN-GB">4</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></li>\r
+ </ul>\r
+ </li>\r
+</ul>\r
+\r
+<h4\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="color:red;mso-ansi-language:EN-GB">Covariates</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h4>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Intercept\r
+and age are systematically included in the model. Additional\r
+covariates can be included with the command <o:p></o:p></span></p>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">model=<em>list of covariates<o:p></o:p></span></em></pre>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l2 level1 lfo15;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">if<strong>\r
+ model=. </strong>then no covariates are included<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l2 level1 lfo15;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">if\r
+ <strong>model=V1</strong> the model includes the first\r
+ covariate (field 2)<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l2 level1 lfo15;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">if\r
+ <strong>model=V2 </strong>the model includes the second\r
+ covariate (field 3)<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l2 level1 lfo15;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">if\r
+ <strong>model=V1+V2 </strong>the model includes the first\r
+ and the second covariate (fields 2 and 3)<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l2 level1 lfo15;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">if\r
+ <strong>model=V1*V2 </strong>the model includes the\r
+ product of the first and the second covariate (fields 2\r
+ and 3)<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l2 level1 lfo15;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">if\r
+ <strong>model=V1+V1*age</strong> the model includes the\r
+ product covariate*age<o:p></o:p></span></li>\r
+</ul>\r
+\r
+<h4\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="color:red;mso-ansi-language:EN-GB">Guess\r
+values for optimisation</span><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB"> </span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h4>\r
+\r
+<p\r
+style="tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">You\r
+must write the initial guess values of the parameters for\r
+optimisation. The number of parameters, <em>N</em> depends on the\r
+number of absorbing states and non-absorbing states and on the\r
+number of covariates. <br>\r
+<em>N</em> is given by the formula <em>N</em>=(<em>nlstate</em> +\r
+<em>ndeath</em>-1)*<em>nlstate</em>*<em>ncov</em> . <br>\r
+<br>\r
+Thus in the simple case with 2 covariates (the model is log\r
+(pij/pii) = aij + bij * age where intercept and age are the two\r
+covariates), and 2 health degrees (1 for disability-free and 2\r
+for disability) and 1 absorbing state (3), you must enter 8\r
+initials values, a12, b12, a13, b13, a21, b21, a23, b23. You can\r
+start with zeros as in this example, but if you have a more\r
+precise set (for example from an earlier run) you can enter it\r
+and it will speed up them<br>\r
+Each of the four lines starts with indices "ij": <b>ij\r
+aij bij</b> <o:p></o:p></span></p>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:\r
+36.0pt;margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"># Guess values of aij and bij in log (pij/pii) = aij + bij * age<o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;\r
+margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">12 -14.155633<span style="mso-spacerun: yes"> </span>0.110794 <o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;\r
+margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">13<span style="mso-spacerun: yes"> </span>-7.925360<span style="mso-spacerun: yes"> </span>0.032091 <o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;\r
+margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">21<span style="mso-spacerun: yes"> </span>-1.890135 -0.029473 <o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;\r
+margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">23<span style="mso-spacerun: yes"> </span>-6.234642<span style="mso-spacerun: yes"> </span>0.022315 <o:p></o:p></span></pre>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">or,\r
+to simplify: <o:p></o:p></span></p>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:\r
+36.0pt;margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">12 0.0 0.0<o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;\r
+margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">13 0.0 0.0<o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:\r
+36.0pt;margin-bottom:0cm;margin-left:36.0pt;margin-bottom:.0001pt;text-align:\r
+justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">21 0.0 0.0<o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;\r
+margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">23 0.0 0.0<o:p></o:p></span></pre>\r
+\r
+<h4\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="color:red;mso-ansi-language:EN-GB">Guess\r
+values for computing variances</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h4>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">This\r
+is an output if </span><a href="#mle"><span lang="EN-GB" style="mso-ansi-language:EN-GB">mle</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a>=1. But it can be used as\r
+an input to get the various output data files (Health\r
+expectancies, stationary prevalence etc.) and figures without\r
+rerunning the rather long maximisation phase (mle=0). <o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">The\r
+scales are small values for the evaluation of numerical\r
+derivatives. These derivatives are used to compute the hessian\r
+matrix of the parameters, that is the inverse of the covariance\r
+matrix, and the variances of health expectancies. Each line\r
+consists in indices "ij" followed by the initial scales\r
+(zero to simplify) associated with aij and bij. <o:p></o:p></span></p>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l16 level1 lfo18;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">If\r
+ mle=1 you can enter zeros:<o:p></o:p></span></li>\r
+</ul>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:\r
+36.0pt;margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"># Scales (for hessian or gradient estimation)<o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;\r
+margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">12 0. 0. <o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:\r
+36.0pt;margin-bottom:0cm;margin-left:36.0pt;margin-bottom:.0001pt;text-align:\r
+justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">13 0. 0. <o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;\r
+margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">21 0. 0. <o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:\r
+36.0pt;margin-bottom:0cm;margin-left:36.0pt;margin-bottom:.0001pt;text-align:\r
+justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">23 0. 0. <o:p></o:p></span></pre>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l11 level1 lfo21;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">If\r
+ mle=0 you must enter a covariance matrix (usually\r
+ obtained from an earlier run).<o:p></o:p></span></li>\r
+</ul>\r
+\r
+<h4\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="color:red;mso-ansi-language:EN-GB">Covariance\r
+matrix of parameters</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h4>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">This\r
+is an output if </span><a href="#mle"><span lang="EN-GB" style="mso-ansi-language:EN-GB">mle</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a>=1. But it can be used as\r
+an input to get the various output data files (Health\r
+expectancies, stationary prevalence etc.) and figures without\r
+rerunning the rather long maximisation phase (mle=0). <o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Each\r
+line starts with indices "ijk" followed by the\r
+covariances between aij and bij: <o:p></o:p></span></p>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"> <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span>121 Var(a12) <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span>122 Cov(b12,a12)<span style="mso-spacerun: yes"> </span>Var(b12) <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span>...<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span>232 Cov(b23,a12)<span style="mso-spacerun: yes"> </span>Cov(b23,b12) ... Var (b23) <o:p></o:p></span></pre>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l18 level1 lfo24;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">If\r
+ mle=1 you can enter zeros. <o:p></o:p></span></li>\r
+</ul>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:\r
+36.0pt;margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"># Covariance matrix<o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;\r
+margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">121 0.<o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:\r
+36.0pt;margin-bottom:0cm;margin-left:36.0pt;margin-bottom:.0001pt;text-align:\r
+justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">122 0. 0.<o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;\r
+margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">131 0. 0. 0. <o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;\r
+margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;margin-bottom:.0001pt;\r
+text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">132 0. 0. 0. 0. <o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;\r
+margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">211 0. 0. 0. 0. 0. <o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;\r
+margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;margin-bottom:.0001pt;\r
+text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">212 0. 0. 0. 0. 0. 0. <o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;\r
+margin-bottom:.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">231 0. 0. 0. 0. 0. 0. 0. <o:p></o:p></span></pre>\r
+\r
+<pre\r
+style="margin-top:\r
+0cm;margin-right:36.0pt;margin-bottom:0cm;margin-left:36.0pt;margin-bottom:\r
+.0001pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">232 0. 0. 0. 0. 0. 0. 0. 0.<o:p></o:p></span></pre>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l7 level1 lfo27;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">If\r
+ mle=0 you must enter a covariance matrix (usually\r
+ obtained from an earlier run).<o:p></o:p></span></li>\r
+</ul>\r
+\r
+<h4\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="color:red;mso-ansi-language:EN-GB">Age\r
+range for calculation of stationary prevalences and health\r
+expectancies</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h4>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">agemin=70 agemax=100 bage=50 fage=100<o:p></o:p></span></pre>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Once\r
+we obtained the estimated parameters, the program is able to\r
+calculated stationary prevalence, transitions probabilities and\r
+life expectancies at any age. Choice of age range is useful for\r
+extrapolation. In our data file, ages varies from age 70 to 102.\r
+Setting bage=50 and fage=100, makes the program computing life\r
+expectancy from age bage to age fage. As we use a model, we can\r
+compute life expectancy on a wider age range than the age range\r
+from the data. But the model can be rather wrong on big\r
+intervals.<o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Similarly,\r
+it is possible to get extrapolated stationary prevalence by age\r
+ranging from agemin to agemax. <o:p></o:p></span></p>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l13 level1 lfo30;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">agemin=</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ Minimum age for calculation of the stationary prevalence <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l13 level1 lfo30;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">agemax=</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ Maximum age for calculation of the stationary prevalence <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l13 level1 lfo30;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">bage=</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ Minimum age for calculation of the health expectancies <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l13 level1 lfo30;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">fage=</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ Maximum age for calculation of the health expectancies <o:p></o:p></span></li>\r
+</ul>\r
+\r
+<h4\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><a\r
+name="Computing"><span lang="EN-GB" style="color:red;mso-ansi-language:EN-GB">Computing</span><span lang="EN-GB" style="color:red;mso-ansi-language:EN-GB"></a> the observed prevalence</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h4>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">begin-prev-date=1/1/1984 end-prev-date=1/6/1988 <o:p></o:p></span></pre>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Statements\r
+'begin-prev-date' and 'end-prev-date' allow to select the period\r
+in which we calculate the observed prevalences in each state. In\r
+this example, the prevalences are calculated on data survey\r
+collected between 1 January 1984 and 1 June 1988. <o:p></o:p></span></p>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l3 level1 lfo33;tab-stops:list 36.0pt"><strong><span lang="EN-GB" style="mso-ansi-language:EN-GB">begin-prev-date=\r
+</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"> </strong>Starting date (day/month/year)<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l3 level1 lfo33;tab-stops:list 36.0pt"><strong><span lang="EN-GB" style="mso-ansi-language:EN-GB">end-prev-date=\r
+</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"> </strong>Final date (day/month/year)<o:p></o:p></span></li>\r
+</ul>\r
+\r
+<h4\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="color:red;mso-ansi-language:EN-GB">Population-\r
+or status-based health expectancies</span><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB"><o:p></o:p></span></h4>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">pop_based=0<o:p></o:p></span></pre>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">The\r
+user has the possibility to choose between population-based or\r
+status-based health expectancies. If pop_based=0 then\r
+status-based health expectancies are computed and if pop_based=1,\r
+the programme computes population-based health expectancies.\r
+Health expectancies are weighted averages of health expectancies\r
+respective of the initial state. For a status-based index, the\r
+weights are the cross-sectional prevalences observed between two\r
+dates, as </span><a href="#Computing"><span lang="EN-GB" style="mso-ansi-language:EN-GB">previously explained</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a>, whereas\r
+for a population-based index, the weights are the stationary\r
+prevalences.<o:p></o:p></span></p>\r
+\r
+<h4\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="color:red;mso-ansi-language:EN-GB">Prevalence\r
+forecasting </span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h4>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">starting-proj-date=1/1/1989 final-proj-date=1/1/1992 mov_average=0 <o:p></o:p></span></pre>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Prevalence\r
+and population projections are available only if the\r
+interpolation unit is a month, i.e. stepm=1. The programme\r
+estimates the prevalence in each state at a precise date\r
+expressed in day/month/year. The programme computes one\r
+forecasted prevalence a year from a starting date (1 January of\r
+1989 in this example) to a final date (1 January 1992). The\r
+statement mov_average allows to compute smoothed forecasted\r
+prevalences with a five-age moving average centred at the mid-age\r
+of the five-age period. <o:p></o:p></span></p>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l10 level1 lfo36;tab-stops:list 36.0pt"><strong><span lang="EN-GB" style="mso-ansi-language:EN-GB">starting-proj-date</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></strong>=\r
+ starting date (day/month/year) of forecasting<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l10 level1 lfo36;tab-stops:list 36.0pt"><strong><span lang="EN-GB" style="mso-ansi-language:EN-GB">final-proj-date=\r
+</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"> </strong>final date (day/month/year) of forecasting<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l10 level1 lfo36;tab-stops:list 36.0pt"><strong><span lang="EN-GB" style="mso-ansi-language:EN-GB">mov_average</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></strong>=\r
+ smoothing with a five-age moving average centred at the\r
+ mid-age of the five-age period. The command<strong>\r
+ mov_average</strong> takes value 1 if the prevalences are\r
+ smoothed and 0 otherwise.<o:p></o:p></span></li>\r
+</ul>\r
+\r
+<h4\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="color:red;mso-ansi-language:EN-GB">Last\r
+uncommented line : Population forecasting </span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h4>\r
+\r
+<pre><span lang="EN-GB" style="mso-ansi-language:EN-GB">popforecast=0 popfile=pyram.txt popfiledate=1/1/1989 last-popfiledate=1/1/1992<o:p></o:p></span></pre>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">This\r
+command is available if the interpolation unit is a month, i.e.\r
+stepm=1 and if popforecast=1. From a data file including age and\r
+number of persons alive at the precise date ‘</span><span lang="EN-GB" style="font-size:10.0pt;mso-bidi-font-size:12.0pt;font-family:"Courier New";\r
+mso-ansi-language:EN-GB">popfiledate’,\r
+</span><span lang="EN-GB" style="mso-ansi-language:EN-GB">you can forecast the number of persons in each state until date</span><span lang="EN-GB" style="font-size:10.0pt;mso-bidi-font-size:\r
+12.0pt;font-family:"Courier New";mso-ansi-language:EN-GB">\r
+‘last-popfiledate’. </span><span lang="EN-GB" style="mso-ansi-language:EN-GB">In this example, the popfile </span><a\r
+href="pyram.txt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">pyram.txt</span><span style="mso-ansi-language:EN-GB"></b></a><b> </span><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB"><span style="mso-spacerun: yes"></b> </span>includes real\r
+data which are the Japanese population in 1989.<span style="mso-spacerun: yes"> </span><o:p></o:p></span></p>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l10 level1 lfo36;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">popforecast=\r
+ 0</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b> Option for population forecasting. If\r
+ popforecast=1, the programme does the forecasting<b>.<o:p></o:p></span></b></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l10 level1 lfo36;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">popfile=\r
+</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"> </b>name of the population file<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l10 level1 lfo36;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">popfiledate=</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>\r
+ date of the population population<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l10 level1 lfo36;tab-stops:list 36.0pt"><b><span lang="EN-GB" style="mso-ansi-language:EN-GB">last-popfiledate</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></b>=\r
+ date of the last population projection <o:p></o:p></span></li>\r
+</ul>\r
+\r
+<hr>\r
+\r
+<h2\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><a\r
+name="running"><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB"></a>Running Imach with this example</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h2>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">We\r
+assume that you entered your </span><a href="biaspar.imach"><span lang="EN-GB" style="mso-ansi-language:EN-GB">1st_example\r
+parameter file</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a> as explained </span><a href="#biaspar"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">above</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a>. To\r
+run the program you should click on the imach.exe icon and enter\r
+the name of the parameter file which is for example </span><a\r
+href="..\mle\biaspar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">C:\usr\imach\mle\biaspar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a> (you\r
+also can click on the biaspar.txt icon located in </span><a\r
+href="..\mle"><span lang="EN-GB" style="mso-ansi-language:EN-GB">C:\usr\imach\mle</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a> and put it with the mouse on\r
+the imach window).<o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">The\r
+time to converge depends on the step unit that you used (1 month\r
+is cpu consuming), on the number of cases, and on the number of\r
+variables.<o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">The\r
+program outputs many files. Most of them are files which will be\r
+plotted for better understanding.<o:p></o:p></span></p>\r
+\r
+<hr>\r
+\r
+<h2\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><a\r
+name="output"><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB">Output of the program and graphs</span><span style="mso-bookmark:output"><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a> </span></span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h2>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Once\r
+the optimization is finished, some graphics can be made with a\r
+grapher. We use Gnuplot which is an interactive plotting program\r
+copyrighted but freely distributed. A gnuplot reference manual is\r
+available </span><a href="http://www.gnuplot.info/"><span lang="EN-GB" style="mso-ansi-language:EN-GB">here</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a>. <br>\r
+When the running is finished, the user should enter a character\r
+for plotting and output editing. <o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">These\r
+characters are:<o:p></o:p></span></p>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l0 level1 lfo41;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">'c'\r
+ to start again the program from the beginning.<o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l0 level1 lfo41;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">'e'\r
+ opens the </span><a href="biaspar.htm"><strong><span lang="EN-GB" style="mso-ansi-language:EN-GB">biaspar.htm</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></strong></a>\r
+ file to edit the output files and graphs. <o:p></o:p></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ text-align:justify;mso-list:l0 level1 lfo41;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">'q'\r
+ for exiting.<o:p></o:p></span></li>\r
+</ul>\r
+\r
+<h5\r
+style="tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="font-size:18.0pt;mso-bidi-font-size:10.0pt;color:#00006A;\r
+mso-ansi-language:EN-GB">Results\r
+files</span><strong><span lang="EN-GB" style="font-size:13.5pt;mso-ansi-language:EN-GB"> </span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></strong><br>\r
+<br>\r
+</span><strong><span lang="EN-GB" style="font-size:12.0pt;color:#EC5E5E;\r
+mso-ansi-language:EN-GB">- </strong><a name="Observed_prevalence_in_each_state"><strong>Observed\r
+prevalence in each state</strong></a><strong> (and at first pass)</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></strong>:\r
+</span><a href="prbiaspar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">prbiaspar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h5>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">The\r
+first line is the title and displays each field of the file. The\r
+first column is age. The fields 2 and 6 are the proportion of\r
+individuals in states 1 and 2 respectively as observed during the\r
+first exam. Others fields are the numbers of people in states 1,\r
+2 or more. The number of columns increases if the number of\r
+states is higher than 2.<br>\r
+The header of the file is <o:p></o:p></span></p>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"># Age Prev(1) N(1) N Age Prev(2) N(2) N<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">70 1.00000 631 631 70 0.00000 0 631<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">71 0.99681 625 627 71 0.00319 2 627 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">72 0.97125 1115 1148 72 0.02875 33 1148 <o:p></o:p></span></pre>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">It\r
+means that at age 70, the prevalence in state 1 is 1.000 and in\r
+state 2 is 0.00 . At age 71 the number of individuals in state 1\r
+is 625 and in state 2 is 2, hence the total number of people aged\r
+71 is 625+2=627. <o:p></o:p></span></p>\r
+\r
+<h5\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="font-size:12.0pt;color:#EC5E5E;mso-ansi-language:EN-GB">-\r
+Estimated parameters and covariance matrix</span><span lang="EN-GB" style="mso-ansi-language:EN-GB">: </span><a\r
+href="rbiaspar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">rbiaspar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h5>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">This\r
+file contains all the maximisation results: <o:p></o:p></span></p>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span>-2 log likelihood= 21660.918613445392<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"> Estimated parameters: a12 = -12.290174 b12 = 0.092161 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span><span style="mso-spacerun: yes"> </span>a13 = -9.155590<span style="mso-spacerun: yes"> </span>b13 = 0.046627 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span>a21 = -2.629849<span style="mso-spacerun: yes"> </span>b21 = -0.022030 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span>a23 = -7.958519<span style="mso-spacerun: yes"> </span>b23 = 0.042614<span style="mso-spacerun: yes"> </span><o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span>Covariance matrix: Var(a12) = 1.47453e-001<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span>Var(b12) = 2.18676e-005<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span>Var(a13) = 2.09715e-001<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span>Var(b13) = 3.28937e-005<span style="mso-spacerun: yes"> </span><o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span>Var(a21) = 9.19832e-001<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span>Var(b21) = 1.29229e-004<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span></span><span lang="DE" style="mso-ansi-language:DE">Var(a23) = 4.48405e-001<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="DE" style="mso-ansi-language:DE"><span style="mso-spacerun: yes"> </span>Var(b23) = 5.85631e-005 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="DE" style="mso-ansi-language:DE"><span style="mso-spacerun: yes"> </span><o:p></o:p></span></pre>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">By\r
+substitution of these parameters in the regression model, we\r
+obtain the elementary transition probabilities:<o:p></o:p></span></p>\r
+\r
+<p\r
+style="tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><img\r
+src="pebiaspar1.gif" width="400" height="300" id="_x0000_i1037"></p>\r
+\r
+<h5\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="font-size:12.0pt;color:#EC5E5E;mso-ansi-language:EN-GB">-\r
+Transition probabilities</span><span lang="EN-GB" style="mso-ansi-language:EN-GB">: </span><a href="pijrbiaspar.txt"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">pijrbiaspar.txt</span><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB"><o:p></o:p></span></a></h5>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Here\r
+are the transitions probabilities Pij(x, x+nh) where nh is a\r
+multiple of 2 years. The first column is the starting age x (from\r
+age 50 to 100), the second is age (x+nh) and the others are the\r
+transition probabilities p11, p12, p13, p21, p22, p23. For\r
+example, line 5 of the file is: <o:p></o:p></span></p>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span>100 106 0.02655 0.17622 0.79722 0.01809 0.13678 0.84513 <o:p></o:p></span></pre>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">and\r
+this means: <o:p></o:p></span></p>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">p11(100,106)=0.02655<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">p12(100,106)=0.17622<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">p13(100,106)=0.79722<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">p21(100,106)=0.01809<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">p22(100,106)=0.13678<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">p22(100,106)=0.84513 <o:p></o:p></span></pre>\r
+\r
+<h5\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="font-size:12.0pt;color:#EC5E5E;mso-ansi-language:EN-GB">-\r
+<a name="Stationary_prevalence_in_each_state">Stationary\r
+prevalence in each state</span><span style="mso-bookmark:Stationary_prevalence_in_each_state"></span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a>: </span><a href="plrbiaspar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">plrbiaspar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h5>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">#Prevalence<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">#Age 1-1 2-2<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"> <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">#************ <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">70 0.90134 0.09866<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">71 0.89177 0.10823 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">72 0.88139 0.11861 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">73 0.87015 0.12985 <o:p></o:p></span></pre>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">At\r
+age 70 the stationary prevalence is 0.90134 in state 1 and\r
+0.09866 in state 2. This stationary prevalence differs from\r
+observed prevalence. Here is the point. The observed prevalence\r
+at age 70 results from the incidence of disability, incidence of\r
+recovery and mortality which occurred in the past of the cohort.\r
+Stationary prevalence results from a simulation with actual\r
+incidences and mortality (estimated from this cross-longitudinal\r
+survey). It is the best predictive value of the prevalence in the\r
+future if "nothing changes in the future". This is\r
+exactly what demographers do with a Life table. Life expectancy\r
+is the expected mean time to survive if observed mortality rates\r
+(incidence of mortality) "remains constant" in the\r
+future. <o:p></o:p></span></p>\r
+\r
+<h5\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="font-size:12.0pt;color:#EC5E5E;mso-ansi-language:EN-GB">-\r
+Standard deviation of stationary prevalence</span><span lang="EN-GB" style="mso-ansi-language:EN-GB">: </span><a\r
+href="vplrbiaspar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">vplrbiaspar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h5>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">The\r
+stationary prevalence has to be compared with the observed\r
+prevalence by age. But both are statistical estimates and\r
+subjected to stochastic errors due to the size of the sample, the\r
+design of the survey, and, for the stationary prevalence to the\r
+model used and fitted. It is possible to compute the standard\r
+deviation of the stationary prevalence at each age.<o:p></o:p></span></p>\r
+\r
+<h5\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="font-size:12.0pt;color:#EC5E5E;mso-ansi-language:EN-GB">-Observed\r
+and stationary prevalence in state (2=disable) with the confident\r
+interval</span><span lang="EN-GB" style="mso-ansi-language:EN-GB">: </span><a href="vbiaspar21.htm"><span lang="EN-GB" style="mso-ansi-language:EN-GB">vbiaspar21.gif</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h5>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">This\r
+graph exhibits the stationary prevalence in state (2) with the\r
+confidence interval in red. The green curve is the observed\r
+prevalence (or proportion of individuals in state (2)). Without\r
+discussing the results (it is not the purpose here), we observe\r
+that the green curve is rather below the stationary prevalence.\r
+It suggests an increase of the disability prevalence in the\r
+future.<o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><img\r
+src="vbiaspar21.gif" width="400" height="300" id="_x0000_i1038"></p>\r
+\r
+<h5\r
+style="tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="font-size:12.0pt;color:#EC5E5E;mso-ansi-language:EN-GB">-Convergence\r
+to the stationary prevalence of disability</span><span lang="EN-GB" style="mso-ansi-language:EN-GB">: </span><a\r
+href="pbiaspar11.gif"><span lang="EN-GB" style="mso-ansi-language:EN-GB">pbiaspar11.gif</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a><br>\r
+</span><img src="pbiaspar11.gif" width="400" height="300"\r
+id="_x0000_i1039"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h5>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">This\r
+graph plots the conditional transition probabilities from an\r
+initial state (1=healthy in red at the bottom, or 2=disable in\r
+green on top) at age <em>x </em>to the final state 2=disable<em> </em>at\r
+age <em>x+h. </em>Conditional means at the condition to be alive\r
+at age <em>x+h </em>which is <i>hP12x</i> + <em>hP22x</em>. The\r
+curves <i>hP12x/(hP12x</i> + <em>hP22x) </em>and <i>hP22x/(hP12x</i>\r
++ <em>hP22x) </em>converge with <em>h, </em>to the <em>stationary\r
+prevalence of disability</em>. In order to get the stationary\r
+prevalence at age 70 we should start the process at an earlier\r
+age, i.e.50. If the disability state is defined by severe\r
+disability criteria with only a few chance to recover, then the\r
+incidence of recovery is low and the time to convergence is\r
+probably longer. But we don't have experience yet.<o:p></o:p></span></p>\r
+\r
+<h5\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="font-size:12.0pt;color:#EC5E5E;mso-ansi-language:EN-GB">-\r
+Life expectancies by age and initial health status</span><span lang="EN-GB" style="mso-ansi-language:EN-GB">: </span><a\r
+href="erbiaspar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">erbiaspar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h5>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"># Health expectancies <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"># Age 1-1 1-2 2-1 2-2 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">70 10.9226 3.0401 5.6488 6.2122 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">71 10.4384 3.0461 5.2477 6.1599 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">72 9.9667 3.0502 4.8663 6.1025 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">73 9.5077 3.0524 4.5044 6.0401 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">For example 70 10.9226 3.0401 5.6488 6.2122 means:<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="DE" style="mso-ansi-language:DE">e11=10.9226 e12=3.0401 e21=5.6488 e22=6.2122<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><img src="expbiaspar21.gif"\r
+width="400" height="300" id="_x0000_i1040"><img\r
+src="expbiaspar11.gif" width="400" height="300" id="_x0000_i1041"></pre>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">For\r
+example, life expectancy of a healthy individual at age 70 is\r
+10.92 in the healthy state and 3.04 in the disability state\r
+(=13.96 years). If he was disable at age 70, his life expectancy\r
+will be shorter, 5.64 in the healthy state and 6.21 in the\r
+disability state (=11.85 years). The total life expectancy is a\r
+weighted mean of both, 13.96 and 11.85; weight is the proportion\r
+of people disabled at age 70. In order to get a pure period index\r
+(i.e. based only on incidences) we use the </span><a\r
+href="#Stationary prevalence in each state"><span lang="EN-GB" style="mso-ansi-language:EN-GB">computed or\r
+stationary prevalence</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a> at age 70 (i.e. computed from\r
+incidences at earlier ages) instead of the </span><a\r
+href="#Observed prevalence in each state"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">observed prevalence</span><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB"></a>\r
+(for example at first exam) (</span><a href="#Health expectancies"><span lang="EN-GB" style="mso-ansi-language:EN-GB">see\r
+below</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a>).<o:p></o:p></span></p>\r
+\r
+<h5\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="font-size:12.0pt;color:#EC5E5E;mso-ansi-language:EN-GB">-\r
+Variances of life expectancies by age and initial health status</span><span lang="EN-GB" style="mso-ansi-language:EN-GB">: </span><a\r
+href="vrbiaspar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">vrbiaspar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h5>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">For\r
+example, the covariances of life expectancies Cov(ei,ej) at age\r
+50 are (line 3) <o:p></o:p></span></p>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span></span><span lang="DE" style="mso-ansi-language:DE">Cov(e1,e1)=0.4776<span style="mso-spacerun: yes"> </span>Cov(e1,e2)=0.0488=Cov(e2,e1)<span style="mso-spacerun: yes"> </span>Cov(e2,e2)=0.0424<o:p></o:p></span></pre>\r
+\r
+<h5\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="font-size:12.0pt;color:#EC5E5E;mso-ansi-language:EN-GB">-\r
+<a name="Health_expectancies">Health expectancies</a> with\r
+standard errors in parentheses</span><span lang="EN-GB" style="mso-ansi-language:EN-GB">: </span><a href="trbiaspar.txt"><span lang="EN-GB" style="font-family:"Courier New";\r
+mso-ansi-language:EN-GB">trbiaspar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h5>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">#Total LEs with variances: e.. (std) e.1 (std) e.2 (std) <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">70 13.76 (0.22) 10.40 (0.20) 3.35 (0.14) <o:p></o:p></span></pre>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Thus,\r
+at age 70 the total life expectancy, e..=13.76years is the\r
+weighted mean of e1.=13.96 and e2.=11.85 by the stationary\r
+prevalence at age 70 which are 0.90134 in state 1 and 0.09866 in\r
+state 2, respectively (the sum is equal to one). e.1=10.40 is the\r
+Disability-free life expectancy at age 70 (it is again a weighted\r
+mean of e11 and e21). e.2=3.35 is also the life expectancy at age\r
+70 to be spent in the disability state.<o:p></o:p></span></p>\r
+\r
+<h5\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="font-size:12.0pt;color:#EC5E5E;mso-ansi-language:EN-GB">-Total\r
+life expectancy by age and health expectancies in states\r
+(1=healthy) and (2=disable)</span><span lang="EN-GB" style="mso-ansi-language:EN-GB">: </span><a href="ebiaspar1.gif"><span lang="EN-GB" style="mso-ansi-language:EN-GB">ebiaspar1.gif</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h5>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">This\r
+figure represents the health expectancies and the total life\r
+expectancy with the confident interval in dashed curve. <o:p></o:p></span></p>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"><span style="mso-spacerun: yes"> </span></span><img\r
+src="ebiaspar1.gif" width="400" height="300" id="_x0000_i1042"></pre>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Standard\r
+deviations (obtained from the information matrix of the model) of\r
+these quantities are very useful. Cross-longitudinal surveys are\r
+costly and do not involve huge samples, generally a few\r
+thousands; therefore it is very important to have an idea of the\r
+standard deviation of our estimates. It has been a big challenge\r
+to compute the Health Expectancy standard deviations. Don't be\r
+confuse: life expectancy is, as any expected value, the mean of a\r
+distribution; but here we are not computing the standard\r
+deviation of the distribution, but the standard deviation of the\r
+estimate of the mean.<o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Our\r
+health expectancies estimates vary according to the sample size\r
+(and the standard deviations give confidence intervals of the\r
+estimate) but also according to the model fitted. Let us explain\r
+it in more details.<o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Choosing\r
+a model means at least two kind of choices. First we have to\r
+decide the number of disability states. Second we have to design,\r
+within the logit model family, the model: variables, covariables,\r
+confounding factors etc. to be included.<o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">More\r
+disability states we have, better is our demographical approach\r
+of the disability process, but smaller are the number of\r
+transitions between each state and higher is the noise in the\r
+measurement. We do not have enough experiments of the various\r
+models to summarize the advantages and disadvantages, but it is\r
+important to say that even if we had huge and unbiased samples,\r
+the total life expectancy computed from a cross-longitudinal\r
+survey, varies with the number of states. If we define only two\r
+states, alive or dead, we find the usual life expectancy where it\r
+is assumed that at each age, people are at the same risk to die.\r
+If we are differentiating the alive state into healthy and\r
+disable, and as the mortality from the disability state is higher\r
+than the mortality from the healthy state, we are introducing\r
+heterogeneity in the risk of dying. The total mortality at each\r
+age is the weighted mean of the mortality in each state by the\r
+prevalence in each state. Therefore if the proportion of people\r
+at each age and in each state is different from the stationary\r
+equilibrium, there is no reason to find the same total mortality\r
+at a particular age. Life expectancy, even if it is a very useful\r
+tool, has a very strong hypothesis of homogeneity of the\r
+population. Our main purpose is not to measure differential\r
+mortality but to measure the expected time in a healthy or\r
+disability state in order to maximise the former and minimize the\r
+latter. But the differential in mortality complexifies the\r
+measurement.<o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Incidences\r
+of disability or recovery are not affected by the number of\r
+states if these states are independant. But incidences estimates\r
+are dependant on the specification of the model. More covariates\r
+we added in the logit model better is the model, but some\r
+covariates are not well measured, some are confounding factors\r
+like in any statistical model. The procedure to "fit the\r
+best model' is similar to logistic regression which itself is\r
+similar to regression analysis. We haven't yet been so far\r
+because we also have a severe limitation which is the speed of\r
+the convergence. On a Pentium III, 500 MHz, even the simplest\r
+model, estimated by month on 8,000 people may take 4 hours to\r
+converge. Also, the program is not yet a statistical package,\r
+which permits a simple writing of the variables and the model to\r
+take into account in the maximisation. The actual program allows\r
+only to add simple variables like age+sex or age+sex+ age*sex but\r
+will never be general enough. But what is to remember, is that\r
+incidences or probability of change from one state to another is\r
+affected by the variables specified into the model.<o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Also,\r
+the age range of the people interviewed has a link with the age\r
+range of the life expectancy which can be estimated by\r
+extrapolation. If your sample ranges from age 70 to 95, you can\r
+clearly estimate a life expectancy at age 70 and trust your\r
+confidence interval which is mostly based on your sample size,\r
+but if you want to estimate the life expectancy at age 50, you\r
+should rely in your model, but fitting a logistic model on a age\r
+range of 70-95 and estimating probabilities of transition out of\r
+this age range, say at age 50 is very dangerous. At least you\r
+should remember that the confidence interval given by the\r
+standard deviation of the health expectancies, are under the\r
+strong assumption that your model is the 'true model', which is\r
+probably not the case.<o:p></o:p></span></p>\r
+\r
+<h5\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="font-size:12.0pt;color:#EC5E5E;mso-ansi-language:EN-GB">-\r
+Copy of the parameter file</span><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">: </span><a href="orbiaspar.txt"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">orbiaspar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h5>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">This\r
+copy of the parameter file can be useful to re-run the program\r
+while saving the old output files. <o:p></o:p></span></p>\r
+\r
+<h5\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="font-size:12.0pt;color:#EC5E5E;mso-ansi-language:EN-GB">-\r
+Prevalence forecasting</span><span lang="EN-GB" style="mso-ansi-language:EN-GB">: </span><a href="frbiaspar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">frbiaspar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></h5>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">First,\r
+we have estimated the observed prevalence between 1/1/1984 and\r
+1/6/1988. <span style="mso-spacerun:\r
+yes"> </span>The mean date of interview (weighed average of\r
+the interviews performed between1/1/1984 and 1/6/1988) is\r
+estimated to be 13/9/1985, as written on the top on the file.\r
+Then we forecast the probability to be in each state. <o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Example,\r
+at date 1/1/1989 : <o:p></o:p></span></p>\r
+\r
+<p class="MsoNormal"><span lang="DE" style="mso-ansi-language:DE"># StartingAge FinalAge P.1 P.2 P.3<o:p></o:p></span></p>\r
+\r
+<p class="MsoNormal"><span lang="EN-GB" style="mso-ansi-language:EN-GB"># Forecasting at date 1/1/1989 <o:p></o:p></span></p>\r
+\r
+<p class="MsoNormal"><span lang="EN-GB" style="mso-ansi-language:EN-GB">73 0.807 0.078 0.115 <o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Since\r
+the minimum age is 70 on the 13/9/1985, the youngest forecasted\r
+age is 73. This means that at age a person aged 70 at 13/9/1989\r
+has a probability to enter state1 of 0.807 at age 73 on 1/1/1989.\r
+Similarly, the probability to be in state 2 is 0.078 and the\r
+probability to die is 0.115. Then, on the 1/1/1989, the\r
+prevalence of disability at age 73 is estimated to be 0.088.<o:p></o:p></span></p>\r
+\r
+<h5\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="font-size:12.0pt;color:#EC5E5E;mso-ansi-language:EN-GB">-\r
+Population forecasting</span><span lang="EN-GB" style="mso-ansi-language:EN-GB">: </span><a href="poprbiaspar.txt"><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">poprbiaspar.txt</span><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB"><o:p></o:p></span></a></h5>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"># Age P.1 P.2 P.3 [Population]<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"># Forecasting at date 1/1/1989 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">75 572685.22 83798.08 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">74 621296.51 79767.99 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">73 645857.70 69320.60 <o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"># Forecasting at date 1/1/1990<o:p></o:p></span></pre>\r
+\r
+<pre style="text-align:justify">76 442986.68 92721.14 120775.48</pre>\r
+\r
+<pre style="text-align:justify">75 487781.02 91367.97 121915.51</pre>\r
+\r
+<pre style="text-align:justify">74 512892.07 85003.47 117282.76 </pre>\r
+\r
+<pre style="text-align:justify"> <o:p></o:p></pre>\r
+\r
+<p class="MsoNormal"><span lang="EN-GB" style="mso-ansi-language:EN-GB">From the population file, we estimate the\r
+number of people in each state. At age 73, 645857 persons are in\r
+state 1 and 69320 are in state 2. One year latter, 512892 are\r
+still in state 1, 85003 are in state 2 and 117282 died before\r
+1/1/1990.<o:p></o:p></span></p>\r
+\r
+<pre style="text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"> <o:p></o:p></span></pre>\r
+\r
+<hr>\r
+\r
+<h2\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><a\r
+name="example"><span lang="EN-GB" style="color:#00006A;mso-ansi-language:EN-GB"></a>Trying an example</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></h2>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Since\r
+you know how to run the program, it is time to test it on your\r
+own computer. Try for example on a parameter file named </span><a\r
+href="..\mytry\imachpar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">imachpar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a> which is a copy of </span><span lang="EN-GB" style="font-size:10.0pt;font-family:"Courier New";mso-ansi-language:EN-GB">mypar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB">\r
+included in the subdirectory of imach, </span><span lang="EN-GB" style="font-size:10.0pt;font-family:"Courier New";\r
+mso-ansi-language:EN-GB">mytry</span><span lang="EN-GB" style="mso-ansi-language:\r
+EN-GB">. Edit it to change\r
+the name of the data file to </span><span lang="EN-GB" style="font-size:10.0pt;font-family:"Courier New";mso-ansi-language:\r
+EN-GB">..\data\mydata.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"> if you don't want\r
+to copy it on the same directory. The file </span><span lang="EN-GB" style="font-family:"Courier New";mso-ansi-language:EN-GB">mydata.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"> is a\r
+smaller file of 3,000 people but still with 4 waves. <o:p></o:p></span></p>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Click\r
+on the imach.exe icon to open a window. Answer to the question: '<strong>Enter\r
+the parameter file name:'<o:p></o:p></span></strong></p>\r
+\r
+<table border="1" cellpadding="0"\r
+style="mso-cellspacing:1.5pt;mso-padding-alt:\r
+ 0cm 0cm 0cm 0cm">\r
+ <tr>\r
+ <td width="100%"\r
+ style="width:100.0%;padding:.75pt .75pt .75pt .75pt"><strong><span lang="EN-GB" style="mso-ansi-language:EN-GB">IMACH,\r
+ Version 0.7</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></strong><p style="text-align:justify"><strong><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB">Enter\r
+ the parameter file name: ..\mytry\imachpar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></strong></p>\r
+ </td>\r
+ </tr>\r
+</table>\r
+\r
+<p\r
+style="tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Most\r
+of the data files or image files generated, will use the\r
+'imachpar' string into their name. The running time is about 2-3\r
+minutes on a Pentium III. If the execution worked correctly, the\r
+outputs files are created in the current directory, and should be\r
+the same as the mypar files initially included in the directory </span><span lang="EN-GB" style="font-size:10.0pt;font-family:"Courier New";mso-ansi-language:EN-GB">mytry</span><span lang="EN-GB" style="mso-ansi-language:EN-GB">.<o:p></o:p></span></p>\r
+\r
+<pre\r
+style="margin-left:36.0pt;text-indent:-18.0pt;mso-list:l5 level1 lfo43"><span lang="EN-GB" style="font-family:Symbol;mso-ansi-language:EN-GB">·<span style="font:7.0pt "Times New Roman""> </span></span><u><span lang="EN-GB" style="mso-ansi-language:EN-GB">Output on the screen</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></u> The output screen looks like </span><a\r
+href="imachrun.LOG"><span lang="EN-GB" style="mso-ansi-language:EN-GB">this Log file</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB"> <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">#title=MLE datafile=..\data\mydata.txt lastobs=3000 firstpass=1 lastpass=3<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">ftol=1.000000e-008 stepm=24 ncov=2 nlstate=2 ndeath=1 maxwav=4 mle=1 weight=0<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Total number of individuals= 2965, Agemin = 70.00, Agemax= 100.92<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB"> <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Warning, no any valid information for:126 line=126<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Warning, no any valid information for:2307 line=2307<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Delay (in months) between two waves Min=21 Max=51 Mean=24.495826<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="font-family:"Times New Roman";mso-ansi-language:EN-GB">These lines give some warnings on the data file and also some raw statistics on frequencies of transitions.</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Age 70 1.=230 loss[1]=3.5% 2.=16 loss[2]=12.5% 1.=222 prev[1]=94.1% 2.=14<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"> prev[2]=5.9% 1-1=8 11=200 12=7 13=15 2-1=2 21=6 22=7 23=1<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Age 102 1.=0 loss[1]=NaNQ% 2.=0 loss[2]=NaNQ% 1.=0 prev[1]=NaNQ% 2.=0 <o:p></o:p></span></pre>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l6 level1 lfo46;tab-stops:list 36.0pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Maximisation\r
+ with the Powell algorithm. 8 directions are given\r
+ corresponding to the 8 parameters. This can be rather\r
+ long to get convergence.<br>\r
+</span><span lang="EN-GB" style="font-size:7.5pt;font-family:"Courier New";\r
+ mso-ansi-language:EN-GB"> <br>\r
+ Powell iter=1 -2*LL=11531.405658264877 1 0.000000000000 2\r
+ 0.000000000000 3<br>\r
+ 0.000000000000 4 0.000000000000 5 0.000000000000 6\r
+ 0.000000000000 7 <br>\r
+ 0.000000000000 8 0.000000000000<br>\r
+ 1..........2.................3..........4.................5.........<br>\r
+ 6................7........8...............<br>\r
+ Powell iter=23 -2*LL=6744.954108371555 1 -12.967632334283\r
+ <br>\r
+ 2 0.135136681033 3 -7.402109728262 4 0.067844593326 <br>\r
+ 5 -0.673601538129 6 -0.006615504377 7 -5.051341616718 <br>\r
+ 8 0.051272038506<br>\r
+ 1..............2...........3..............4...........<br>\r
+ 5..........6................7...........8.........<br>\r
+ #Number of iterations = 23, -2 Log likelihood =\r
+ 6744.954042573691<br>\r
+ # Parameters<br>\r
+ 12 -12.966061 0.135117 <br>\r
+ 13 -7.401109 0.067831 <br>\r
+ 21 -0.672648 -0.006627 <br>\r
+ 23 -5.051297 0.051271 </span><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB"><o:p></o:p></span></li>\r
+</ul>\r
+\r
+<pre\r
+style="margin-left:36.0pt;text-align:justify;text-indent:-18.0pt;\r
+mso-list:l6 level1 lfo46"><span lang="EN-GB" style="font-family:Symbol;mso-ansi-language:EN-GB">·<span style="font:7.0pt "Times New Roman""> </span></span><span lang="EN-GB" style="mso-ansi-language:EN-GB">Calculation of the hessian matrix. Wait...<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">12345678.12.13.14.15.16.17.18.23.24.25.26.27.28.34.35.36.37.38.45.46.47.48.56.57.58.67.68.78<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"> <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Inverting the hessian to get the covariance matrix. </span>Wait...</pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"> <o:p></o:p></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify">#Hessian matrix#</pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="DE" style="mso-ansi-language:DE">3.344e+002 2.708e+004 -4.586e+001 -3.806e+003 -1.577e+000 -1.313e+002 3.914e-001 3.166e+001 <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="DE" style="mso-ansi-language:DE">2.708e+004 2.204e+006 -3.805e+003 -3.174e+005 -1.303e+002 -1.091e+004 2.967e+001 2.399e+003 <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="DE" style="mso-ansi-language:DE">-4.586e+001 -3.805e+003 4.044e+002 3.197e+004 2.431e-002 1.995e+000 1.783e-001 1.486e+001 <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="DE" style="mso-ansi-language:DE">-3.806e+003 -3.174e+005 3.197e+004 2.541e+006 2.436e+000 2.051e+002 1.483e+001 1.244e+003 <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="DE" style="mso-ansi-language:DE">-1.577e+000 -1.303e+002 2.431e-002 2.436e+000 1.093e+002 8.979e+003 -3.402e+001 -2.843e+003 <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="DE" style="mso-ansi-language:DE">-1.313e+002 -1.091e+004 1.995e+000 2.051e+002 8.979e+003 7.420e+005 -2.842e+003 -2.388e+005 <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="DE" style="mso-ansi-language:DE">3.914e-001 2.967e+001 1.783e-001 1.483e+001 -3.402e+001 -2.842e+003 1.494e+002 1.251e+004 <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt"><span lang="DE" style="mso-ansi-language:DE">3.166e+001 2.399e+003 1.486e+001 1.244e+003 -2.843e+003 -2.388e+005 1.251e+004 1.053e+006 <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="DE" style="mso-ansi-language:\r
+DE"># Scales<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:\r
+justify"><span lang="DE" style="mso-ansi-language:DE">12 1.00000e-004 1.00000e-006<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="DE" style="mso-ansi-language:\r
+DE">13 1.00000e-004 1.00000e-006<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:\r
+18.0pt;text-align:justify"><span lang="DE" style="mso-ansi-language:DE">21 1.00000e-003 1.00000e-005<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="DE" style="mso-ansi-language:\r
+DE">23 1.00000e-004 1.00000e-005<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:\r
+18.0pt;text-align:justify"><span lang="DE" style="mso-ansi-language:DE"># Covariance<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="DE" style="mso-ansi-language:\r
+DE"><span style="mso-spacerun: yes"> </span>1 5.90661e-001<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="DE" style="mso-ansi-language:\r
+DE"><span style="mso-spacerun: yes"> </span>2 -7.26732e-003 8.98810e-005<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="DE" style="mso-ansi-language:\r
+DE"><span style="mso-spacerun: yes"> </span>3 8.80177e-002 -1.12706e-003 5.15824e-001<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="DE" style="mso-ansi-language:\r
+DE"><span style="mso-spacerun: yes"> </span>4 -1.13082e-003 1.45267e-005 -6.50070e-003 8.23270e-005<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="DE" style="mso-ansi-language:\r
+DE"><span style="mso-spacerun: yes"> </span>5 9.31265e-003 -1.16106e-004 6.00210e-004 -8.04151e-006 1.75753e+000<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="DE" style="mso-ansi-language:\r
+DE"><span style="mso-spacerun: yes"> </span>6 -1.15664e-004 1.44850e-006 -7.79995e-006 1.04770e-007 -2.12929e-002 2.59422e-004<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="DE" style="mso-ansi-language:\r
+DE"><span style="mso-spacerun: yes"> </span>7 1.35103e-003 -1.75392e-005 -6.38237e-004 7.85424e-006 4.02601e-001 -4.86776e-003 1.32682e+000<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="DE" style="mso-ansi-language:\r
+DE"><span style="mso-spacerun: yes"> </span>8 -1.82421e-005 2.35811e-007 7.75503e-006 -9.58687e-008 -4.86589e-003 5.91641e-005 -1.57767e-002 1.88622e-004<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"># agemin agemax for lifexpectancy, bage fage (if mle==0 ie no data nor Max likelihood).<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"> <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB"> <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">agemin=70 agemax=100 bage=50 fage=100<o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Computing prevalence limit: result on file 'plrmypar.txt' <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Computing pij: result on file 'pijrmypar.txt' <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Computing Health Expectancies: result on file 'ermypar.txt' <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Computing Variance-covariance of DFLEs: file 'vrmypar.txt' <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Computing Total LEs with variances: file 'trmypar.txt' <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Computing Variance-covariance of Prevalence limit: file 'vplrmypar.txt' <o:p></o:p></span></pre>\r
+\r
+<pre style="margin-left:18.0pt;text-align:justify"><span lang="EN-GB" style="mso-ansi-language:EN-GB">End of Imach<o:p></o:p></span></pre>\r
+\r
+<p\r
+style="text-align:justify;tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Once\r
+the running is finished, the program requires a caracter:<o:p></o:p></span></p>\r
+\r
+<table border="1" cellpadding="0"\r
+style="mso-cellspacing:1.5pt;mso-padding-alt:\r
+ 0cm 0cm 0cm 0cm">\r
+ <tr>\r
+ <td width="100%"\r
+ style="width:100.0%;padding:.75pt .75pt .75pt .75pt"><strong><span lang="EN-GB" style="mso-ansi-language:EN-GB">Type\r
+ e to edit output files, c to start again, and q for\r
+ exiting:</span><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB"><o:p></o:p></span></strong></td>\r
+ </tr>\r
+</table>\r
+\r
+<p\r
+style="tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">First\r
+you should enter <strong>e </strong>to edit the master file\r
+mypar.htm. <o:p></o:p></span></p>\r
+\r
+<ul type="disc">\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l9 level1 lfo49;tab-stops:list 36.0pt"><u><span lang="EN-GB" style="mso-ansi-language:EN-GB">Outputs\r
+ files</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></u> <br>\r
+ <br>\r
+ - Observed prevalence in each state: </span><a\r
+ href="..\mytry\prmypar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">pmypar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a> <br>\r
+ - Estimated parameters and the covariance matrix: </span><a\r
+ href="..\mytry\rmypar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">rmypar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a> <br>\r
+ - Stationary prevalence in each state: </span><a\r
+ href="..\mytry\plrmypar.txt"><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB">plrmypar.txt</span><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB"></a> <br>\r
+ - Transition probabilities: </span><a\r
+ href="..\mytry\pijrmypar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">pijrmypar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a> <br>\r
+ - Copy of the parameter file: </span><a\r
+ href="..\mytry\ormypar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">ormypar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a> <br>\r
+ - Life expectancies by age and initial health status: </span><a\r
+ href="..\mytry\ermypar.txt"><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB">ermypar.txt</span><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB"></a> <br>\r
+ - Variances of life expectancies by age and initial\r
+ health status: </span><a href="..\mytry\vrmypar.txt"><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB">vrmypar.txt</span><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB"></a>\r
+ <br>\r
+ - Health expectancies with their variances: </span><a\r
+ href="..\mytry\trmypar.txt"><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB">trmypar.txt</span><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB"></a> <br>\r
+ - Standard deviation of stationary prevalence: </span><a\r
+ href="..\mytry\vplrmypar.txt"><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB">vplrmypar.txt</span><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB"></a><br>\r
+ - Prevalences forecasting: </span><a href="frmypar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">frmypar.txt</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a>\r
+ <br>\r
+ - Population forecasting (if popforecast=1): </span><a\r
+ href="poprmypar.txt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">poprmypar.txt</span><span style="mso-ansi-language:EN-GB"></a> <span lang="EN-GB"><o:p></o:p></span></span></li>\r
+ <li class="MsoNormal"\r
+ style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;\r
+ mso-list:l9 level1 lfo49;tab-stops:list 36.0pt"><u><span lang="EN-GB" style="mso-ansi-language:EN-GB">Graphs</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></u>\r
+ <br>\r
+ <br>\r
+ -</span><a href="..\mytry\pemypar1.gif"><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB">One-step transition\r
+ probabilities</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a><br>\r
+ -</span><a href="..\mytry\pmypar11.gif"><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB">Convergence to the\r
+ stationary prevalence</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a><br>\r
+ -</span><a href="..\mytry\vmypar11.gif"><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB">Observed and stationary\r
+ prevalence in state (1) with the confident interval</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a> <br>\r
+ -</span><a href="..\mytry\vmypar21.gif"><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB">Observed and stationary\r
+ prevalence in state (2) with the confident interval</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a> <br>\r
+ -</span><a href="..\mytry\expmypar11.gif"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Health life\r
+ expectancies by age and initial health state (1)</span><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB"></a> <br>\r
+ -</span><a href="..\mytry\expmypar21.gif"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Health life\r
+ expectancies by age and initial health state (2)</span><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB"></a> <br>\r
+ -</span><a href="..\mytry\emypar1.gif"><span lang="EN-GB" style="mso-ansi-language:\r
+ EN-GB">Total life expectancy by\r
+ age and health expectancies in states (1) and (2).</span><span style="mso-ansi-language:EN-GB"></a> <span lang="EN-GB"><o:p></o:p></span></span></li>\r
+</ul>\r
+\r
+<p\r
+style="tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">This\r
+software have been partly granted by </span><a\r
+href="http://euroreves.ined.fr"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Euro-REVES</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a>, a concerted\r
+action from the European Union. It will be copyrighted\r
+identically to a GNU software product, i.e. program and software\r
+can be distributed freely for non commercial use. Sources are not\r
+widely distributed today. You can get them by asking us with a\r
+simple justification (name, email, institute) </span><a\r
+href="mailto:brouard@ined.fr"><span lang="EN-GB" style="mso-ansi-language:EN-GB">mailto:brouard@ined.fr</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a> and </span><a\r
+href="mailto:lievre@ined.fr"><span lang="EN-GB" style="mso-ansi-language:EN-GB">mailto:lievre@ined.fr</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"></a> .<o:p></o:p></span></p>\r
+\r
+<p\r
+style="tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt"><span lang="EN-GB" style="mso-ansi-language:EN-GB">Latest\r
+version (0.7 of February 2002) can be accessed at </span><a\r
+href="http://euroreves.ined.fr/imach"><span lang="EN-GB" style="mso-ansi-language:EN-GB">http://euroreves.ined.fr/imach</span><span lang="EN-GB" style="mso-ansi-language:EN-GB"><o:p></o:p></span></a></p>\r
+</body>\r
+</html>\r
git://henry.ined.fr / .git / commitdiff