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version 1.7, 2002/03/10 15:54:47
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version 1.8, 2002/03/11 14:18:06
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| <title>Computing Health Expectancies using IMaCh</title>
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<title>Computing Health Expectancies using IMaCh</title>
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| <!-- Changed by: Agnes Lievre, 12-Oct-2000 -->
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<!-- Changed by: Agnes Lievre, 12-Oct-2000 -->
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Line 320 line</font></a></h4>
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Line 327 line</font></a></h4>
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| <li>... </li>
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<li>... </li>
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| </ul>
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</ul>
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| </li>
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</li>
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| <li><b>ncov=2</b> Number of covariates in the datafile. The
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<li><b>ncov=2</b> Number of covariates in the datafile. </li>
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| intercept and the age parameter are counting for 2
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| covariates.</li>
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| <li><b>nlstate=2</b> Number of non-absorbing (alive) states.
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<li><b>nlstate=2</b> Number of non-absorbing (alive) states.
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| Here we have two alive states: disability-free is coded 1
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Here we have two alive states: disability-free is coded 1
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| and disability is coded 2. </li>
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and disability is coded 2. </li>
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Line 348 line</font></a></h4>
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Line 353 line</font></a></h4>
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| <h4><font color="#FF0000">Covariates</font></h4>
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<h4><font color="#FF0000">Covariates</font></h4>
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| <p>Intercept and age are systematically included in the model.
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<p>Intercept and age are systematically included in the model.
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| Additional covariates (actually two) can be included with the command: </p>
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Additional covariates can be included with the command: </p>
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| <pre>model=<em>list of covariates</em></pre>
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<pre>model=<em>list of covariates</em></pre>
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Line 368 Additional covariates (actually two) can
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Line 373 Additional covariates (actually two) can
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| the product covariate*age</li>
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the product covariate*age</li>
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</ul>
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<p>In this example, we have two covariates in the data file
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(fields 2 and 3). The number of covariates is defined with
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statement ncov=2. If now you have 3 covariates in the datafile
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(fields 2, 3 and 4), you have to set ncov=3. Then you can run the
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programme with a new parametrisation taking into account the
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third covariate. For example, <strong>model=V1+V3 </strong>estimates
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a model with the first and third covariates. More complicated
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models can be used, but it will takes more time to converge. With
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a simple model (no covariates), the programme estimates 8
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parameters. Adding covariates increases the number of parameters
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: 12 for <strong>model=V1, </strong>16 for <strong>model=V1+V1*age
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</strong>and 20 for <strong>model=V1+V2+V3.</strong></p>
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| <h4><font color="#FF0000">Guess values for optimization</font><font
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<h4><font color="#FF0000">Guess values for optimization</font><font
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| color="#00006A"> </font></h4>
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color="#00006A"> </font></h4>
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Line 397 aij bij</b> </p>
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Line 415 aij bij</b> </p>
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| 23 -6.234642 0.022315 </pre>
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23 -6.234642 0.022315 </pre>
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| </blockquote>
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</blockquote>
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| <p>or, to simplify (in most of cases it converges but there is no warranty!): </p>
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<p>or, to simplify (in most of cases it converges but there is no
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warranty!): </p>
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| <blockquote>
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<blockquote>
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| <pre>12 0.0 0.0
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<pre>12 0.0 0.0
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Line 484 prevalences and health expectancies</fon
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Line 503 prevalences and health expectancies</fon
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| to calculated stationary prevalence, transitions probabilities
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to calculated stationary prevalence, transitions probabilities
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| and life expectancies at any age. Choice of age range is useful
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and life expectancies at any age. Choice of age range is useful
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| for extrapolation. In our data file, ages varies from age 70 to
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for extrapolation. In our data file, ages varies from age 70 to
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| 102. It is possible to get extrapolated stationary
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102. It is possible to get extrapolated stationary prevalence by
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| prevalence by age ranging from agemin to agemax. </p>
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age ranging from agemin to agemax. </p>
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<p>Setting bage=50 (begin age) and fage=100 (final age), makes
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| <p>Setting bage=50 (begin age) and fage=100 (final age), makes the program computing
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the program computing life expectancy from age 'bage' to age
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| life expectancy from age 'bage' to age 'fage'. As we use a model, we
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'fage'. As we use a model, we can interessingly compute life
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| can interessingly compute life expectancy on a wider age range than the age
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expectancy on a wider age range than the age range from the data.
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| range from the data. But the model can be rather wrong on much larger
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But the model can be rather wrong on much larger intervals.
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| intervals. Program is limited to around 120 for upper age!</p>
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Program is limited to around 120 for upper age!</p>
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| <ul>
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<ul>
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| <li><b>agemin=</b> Minimum age for calculation of the
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<li><b>agemin=</b> Minimum age for calculation of the
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Line 527 expectancies</font></h4>
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Line 546 expectancies</font></h4>
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| <pre>pop_based=0</pre>
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<pre>pop_based=0</pre>
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| <p>The program computes status-based health expectancies, i.e health
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<p>The program computes status-based health expectancies, i.e
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| expectancies which depends on your initial health state. If you are
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health expectancies which depends on your initial health state.
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| healthy your healthy life expectancy (e11) is higher than if you were
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If you are healthy your healthy life expectancy (e11) is higher
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| disabled (e21, with e11 > e21).<br>
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than if you were disabled (e21, with e11 > e21).<br>
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| To compute a healthy life expectancy independant of the initial status
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To compute a healthy life expectancy independant of the initial
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| we have to weight e11 and e21 according to the probability to be in
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status we have to weight e11 and e21 according to the probability
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| each state at initial age or, with other word, according to the
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to be in each state at initial age or, with other word, according
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| proportion of people in each state.<br>
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to the proportion of people in each state.<br>
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We prefer computing a 'pure' period healthy life expectancy based
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| We prefer computing a 'pure' period healthy life expectancy based only
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only on the transtion forces. Then the weights are simply the
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| on the transtion forces. Then the weights are simply the stationnary
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stationnary prevalences or 'implied' prevalences at the initial
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| prevalences or 'implied' prevalences at the initial age.<br>
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age.<br>
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Some other people would like to use the cross-sectional
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| Some other people would like to use the cross-sectional prevalences
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prevalences (the "Sullivan prevalences") observed at
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| (the "Sullivan prevalences") observed at the initial age during a
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the initial age during a period of time <a href="#Computing">defined
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| period of time <a href="#Computing">defined just above</a>.
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just above</a>. </p>
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| <ul>
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<ul>
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| <li><strong>popbased= 0 </strong> Health expectancies are computed
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<li><strong>popbased= 0 </strong>Health expectancies are
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| at each age from stationary prevalences 'expected' at this initial age.</li>
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computed at each age from stationary prevalences
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| <li><strong>popbased= 1 </strong> Health expectancies are computed
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'expected' at this initial age.</li>
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| at each age from cross-sectional 'observed' prevalence at this
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<li><strong>popbased= 1 </strong>Health expectancies are
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| initial age. As all the population is not observed at the same exact date we
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computed at each age from cross-sectional 'observed'
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| define a short period were the observed prevalence is computed.</li>
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prevalence at this initial age. As all the population is
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not observed at the same exact date we define a short
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period were the observed prevalence is computed.</li>
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| </ul>
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</ul>
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| </p>
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| <h4><font color="#FF0000">Prevalence forecasting ( Experimental)</font></h4>
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<h4><font color="#FF0000">Prevalence forecasting ( Experimental)</font></h4>
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| <pre>starting-proj-date=1/1/1989 final-proj-date=1/1/1992 mov_average=0 </pre>
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<pre>starting-proj-date=1/1/1989 final-proj-date=1/1/1992 mov_average=0 </pre>
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| <p>Prevalence and population projections are only available if the
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<p>Prevalence and population projections are only available if
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| interpolation unit is a month, i.e. stepm=1 and if there are no
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the interpolation unit is a month, i.e. stepm=1 and if there are
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| covariate. The programme estimates the prevalence in each state at a
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no covariate. The programme estimates the prevalence in each
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| precise date expressed in day/month/year. The programme computes one
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state at a precise date expressed in day/month/year. The
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| forecasted prevalence a year from a starting date (1 january of 1989
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programme computes one forecasted prevalence a year from a
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| in this example) to a final date (1 january 1992). The statement
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starting date (1 january of 1989 in this example) to a final date
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| mov_average allows to compute smoothed forecasted prevalences with a
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(1 january 1992). The statement mov_average allows to compute
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| five-age moving average centered at the mid-age of the five-age
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smoothed forecasted prevalences with a five-age moving average
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| period. </p>
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centered at the mid-age of the five-age period. </p>
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| <ul>
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<ul>
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| <li><strong>starting-proj-date</strong>= starting date
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<li><strong>starting-proj-date</strong>= starting date
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Line 1000 are in state 2. One year latter, 512892
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Line 1019 are in state 2. One year latter, 512892
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| <hr>
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<hr>
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| <h2><a name="example"> </a><font color="#00006A">Trying an example</font></a></h2>
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<h2><a name="example"></a><font color="#00006A">Trying an example</font></h2>
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| <p>Since you know how to run the program, it is time to test it
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<p>Since you know how to run the program, it is time to test it
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| on your own computer. Try for example on a parameter file named <a
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on your own computer. Try for example on a parameter file named <a
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Line 1191 href="mailto:brouard@ined.fr">mailto:bro
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Line 1210 href="mailto:brouard@ined.fr">mailto:bro
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| href="mailto:lievre@ined.fr">mailto:lievre@ined.fr</a> .</p>
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href="mailto:lievre@ined.fr">mailto:lievre@ined.fr</a> .</p>
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| <p>Latest version (0.71a of March 2002) can be accessed at <a
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<p>Latest version (0.71a of March 2002) can be accessed at <a
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| href="http://euroeves.ined.fr/imach">http://euroreves.ined.fr/imach</a><br>
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href="http://euroreves.ined.fr/imach">http://euroreves.ined.fr/imach</a><br>
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| </p>
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</p>
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