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File of contributions to the likelihood: %s
Powell pow# Powell # iter -2*LL p%1d%1d #Number of iterations = %d, -2 Log likelihood = %.12f #Number of iterations = %d, -2 Log likelihood = %.12f #Number of iterations = %d, -2 Log likelihood = %.12f Calculation of the hessian matrix. Wait... .%d%d Inverting the hessian to get the covariance matrix. Wait... #Hessian matrix# %.3e -C6?$@@@@Singular matrix in routine ludcmp#B ;pProblem with prevalence resultfile: %s #********** Variable V%d=%d ********** # Age Prev(%d) N(%d) NTotalSee log file for details... Age %d %d.=%.0f loss[%d]=%.1f%% %d.=%.0f loss[%d]=NaNQ%% %d.=%.0f prev[%d]=%.1f%% %d.=%.0f prev[%d]=NaNQ%% %d %.5f %.0f %.0f %d NaNq %.0f %.0f %d%d=%.0fOthers in log... (@|=Y@h㈵>Error on individual =%d agev[m][i]=%f m=%d (@h㈵>Warning! None valid information for:%ld line=%d (skipped) and may be others, see log file Warning! None valid information for:%ld line=%d (skipped) Error! Negative delay (%d to death) between waves %d and %d of individual %ld at line %d who is aged %.1f with statuses from %d to %d We assumed that the date of interview was correct (and not the date of death) and postponed the death %d month(s) (one stepm) after the interview. You MUST fix the contradiction between dates. Error! Negative delay (%d) between waves %d and %d of individual %ld at line %d who is aged %.1f with statuses from %d to %d Delay (in months) between two waves Min=%d Max=%d Mean=%f @p@(@?# Health expectancies # Age %1d-%1d (SE)Problem %d lower than %d %d|%3.0f %9.4f (%.4f)@`@(@?@-populbased-mobilav--populbased-nomobil--stablbased- Error in movingaverage mobilav=%d prmorprev%-dComputing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' # probabilities of dying before estepm=%d months for people of exact age and weighted probabilities w1*p1j+w2*p2j+... stand dev in() # Age cov=%-d p.%-d SE w%1d p%-d%-d # Routine varevsij

  • Computing probabilities of dying over estepm months as a weighted average (i.e global mortality independent of initial healh state)


    • %s
    # Variance and covariance of health expectancies e.j # (weighted average of eij where weights are the stable prevalence in health states i Cov(e%1d, e%1d)%3d %d %11.3e %11.3e %11.3e %11.3e %.0f %.4f set noparametric;set nolabel; set ter png small;set size 0.65, 0.65 set log y; set nolog x;set xlabel "Age"; set ylabel "Force of mortality (year-1)"; plot "%s" u 1:($3) not w l 1 replot "%s" u 1:(($3+1.96*$4)) t "95%% interval" w l 2 replot "%s" u 1:(($3-1.96*$4)) not w l 2
    File (multiple files are possible if covariates are present): %s varmuptjgr
    Probability is computed over estepm=%d months.

    set out "%s%s.png";replot; @`@(@?@# Standard deviation of stable prevalences %1d-%1d %.5f (%.5f)@`@(@?@probprobcovprobcorComputing standard deviation of one-step probabilities: result on file '%s' Computing matrix of variance covariance of one-step probabilities: result on file '%s' and correlation matrix of one-step probabilities: result on file '%s' #One-step probabilities and stand. devi in () #One-step probabilities and covariance matrix #One-step probabilities and correlation matrix p%1d-%1d (SE) p%1d-%1d # Routine varprob

  • Computing and drawing one step probabilities with their confidence intervals

  • Matrix of variance-covariance of pairs of step probabilities (drawings)

    • Matrix of variance-covariance of pairs of step probabilities

    file %s
    Ellipsoids of confidence centered on point (pij, pkl) are estimatedand drawn. It helps understanding how is the covariance between two incidences. They are expressed in year-1 in order to be less dependent of stepm.

    Contour plot corresponding to x'cov-1x = 4 (where x is the column vector (pij,pkl)) are drawn. It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 standard deviations wide on each axis.
    Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix and made the appropriate rotation to look at the uncorrelated principal directions.
    To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.
    ********** # V%d=%d
    ********** Variable **********
    %d %11.3e (%11.3e) %11.3e %d %d-%d %11.3e%d %d%d-%d%d mu %.4e %.4e Var %.4e %.4e cor %.3f cov %.4e Eig %.3e %.3e 1stv %.3f %.3f tang %.3f Others in log... %d %d%d-%d%d mu %.4e %.4e Var %.4e %.4e cor %.3f cov %.4e Eig %.3e %.3e 1stv %.3f %.3f tan %.3f set parametric;unset label set log y;set log x; set xlabel "p%1d%1d (year-1)";set ylabel "p%1d%1d (year-1)" set ter png small set size 0.65,0.65varpijgr
    Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year-1 :%s%d%1d%1d-%1d%1d.png,

    Correlation at age %d (%.3f), set out "%s%d%1d%1d-%1d%1d.png" set label "%d" at %11.3e,%11.3e center # Age %d, p%1d%1d - p%1d%1d plot [-pi:pi] %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not %d (%.3f), replot %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not set out "%s%d%1d%1d-%1d%1d.png";replot;@(@@

    • Result files (first order: no variance)

      - Observed prevalence in each state (during the period defined between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf): %s
      pij - Estimated transition probabilities over %d (stepm) months: %s
      pl - Stable prevalence in each health state: %s
      e - Life expectancies by age and initial health status (estepm=%2d months): %s
      • Graphs

        • ************ Results for covariates ************
        pe
        - Pij or Conditional probabilities to be observed in state j being in state i, %d (stepm) months before: %s%d1.png

        - Pij or Conditional probabilities to be observed in state j being in state i %d (stepm) months before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too: %s%d2.png

        - Stable prevalence in each health state : p%s%d%d.png
        exp
        - Health life expectancies by age and initial health state (%d): %s%d%d.png

    • Result files (second order: variances)

      - Parameter file with estimated parameters and covariance matrix: %s
      - Variance of one-step probabilities: %s
      - Variance-covariance of one-step probabilities: %s
      - Correlation matrix of one-step probabilities: %s
      v - Variances and covariances of life expectancies by age and initial health status (estepm=%d months): %s
      t - Health expectancies with their variances (no covariance): %s
      vpl - Standard deviation of stable prevalences: %s
      • Graphs


        • - Observed (cross-sectional) and period (incidence based) prevalence (with 95%% confidence interval) in state (%d): %s%d%d.png

        - Total life expectancy by age and health expectancies in states (1) and (2): %s%d.png
        cd "%s" set out "%s%d%d.png" #set out "v%s%d%d.png" set xlabel "Age" set ylabel "Probability" set ter png small set size 0.65,0.65 plot [%.f:%.f] "%s" every :::%d::%d u 1:2 "%%lf %%lf (%%lf) %%*lf (%%*lf)" t"Stable prevalence" w l 0,"%s" every :::%d::%d u 1:($2+1.96*$3) "%%lf" t"95%% CI" w l 1,"%s" every :::%d::%d u 1:($2-1.96*$3) "%%lf" t"" w l 1,"%s" every :::%d::%d u 1:($%d) t"Observed prevalence " w l 2 set out "%s%d.png" set ylabel "Years" set ter png small set size 0.65,0.65 plot [%.f:%.f] "%s" every :::%d::%d u 1:2 "%%lf" t"TLE" w l ," t"LE in state (%d)" w l ,"%s" every :::%d::%d u 1:($2-$3*2) "%%lf" t"" w l 0,"%s" every :::%d::%d u 1:($2+$3*2) "%%lf" t"" w l 0set ter png small set size 0.65,0.65 plot [%.f:%.f] "%s" every :::%d::%d u 1:%d t "e%d1" w l ,"%s" every :::%d::%d u 1:%d t "e%d%d" w lset xlabel "Age" set ylabel "Probability" set ter png small set size 0.65,0.65 unset log y plot [%.f:%.f] "%s" u ($1==%d ? ($3):1/0):($%d/($%d+$%d)) t"prev(%d,%d)" w l,"%s" u ($1==%d ? ($3):1/0):($%d/($%d)) t"prev(%d,%d)" w l p%d=%f set ylabel "Quasi-incidence per year" set title "Probability" set ter png small set size 0.65,0.65 set log y plot [%.f:%.f] %f*exp(p%d+p%d*x exp(p%d+p%d*x+p%d*%d*x+p%d*%d)/(1+exp(p%d+p%d*x)) t "p%d%d" ,@(@fProblem with forecast resultfile: %s Computing forecasting: result on file '%s' # Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f #****** Routine prevforecast ** #****** V%d=%d, hpijx=probability over h years, hp.jx is weighted by observed prev ****** # Covariate valuofcovar yearproj age p%d%d p.%d # Forecasting at date %.lf/%.lf/%.lf %d %d %.f %.f %.3f@`@(@>@?poprProblem with population file : %s %d %lf P.%d [Population] # Forecasting at date %.lf/%.lf/%.lf %3.f %15.2f@`@(@v@?aProblem with file: %s # Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ... %1d%1d 0.# Scales (for hessian or gradient estimation) # Covariance matrix #%1d%1d%d%1d%1d%d Cov(%s%1d%1d,%s%1d%1d) Var(%s%1d%1d)(@.@

        • Result files

          Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):
          mu(age) =%lf*exp(%lf*(age-%d)) per year

          p[%d] = %lf [%f ; %f]


          set out "graphmort.png" set xlabel "Age" set ylabel "Force of mortality (per year)" set ter png small set log y set size 0.65,0.65 plot [%d:100] %lf*exp(%lf*(x-%d))bcdc %s %s Enter the parameter file name: %spathimach=%s, pathtot=%s, path=%s, optionfile=%s optionfilext=%s optionfilefiname=%s mkdir Problem creating directory or it already exists %s%s, err=%d .logProblem with logfile %s Log filename:%s Enter the parameter file name: pathimach=%s pathtot=%s path=%s optionfile=%s optionfilext=%s optionfilefiname=%s Local time (at start):%sLocal time (at start): %s.txtProblem with optionfile %s oProblem with Output resultfile: %s title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d ftol=%lf stepm=%d ncovcol=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d model=%s title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d ftol=%e stepm=%d ncovcol=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d model=%s You choose mle=-1, look at file %s for a template of covariance matrix You choose mle=-3, look at file %s for a template of covariance matrix Error in line parameters number %d, %1d%1d instead of %1d%1d %lf%le %le %.5leProblem writing new parameter file: %s #%s Problem with datafile: %s ageage*ageError. Non available option model=%s Error! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown, you must set an arbitrary year of death or he/she is skipped and results are biased Error! Month of death of individual %ld on line %d was unknown %2d, you should set it otherwise the information on the death is skipped and results are biased. Error! Month of death of individual %ld on line %d was unknown %f, you should set it otherwise the information on the death is skipped and results are biased. Warning negative age at death: %ld line:%d Error: on wave %d of individual %d status %d > (nlstate+ndeath)=(%d+%d)=%d Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f -mort.gpProblem with file %s # %s # %s set missing 'NaNq' .htmProblem with %s -cov.htm IMaCh Cov %s %s
          %s
          Title=%s
          Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=%s
          IMaCh %s %s
          %s
          Title=%s
          Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=%s

          • Parameter files

            - Copy of the parameter file: o%s
            - Log file of the run: %s
            - Gnuplot file name: %s
            - Date and time at start: %s

          Total number of observations=%d
          Youngest age at first (selected) pass %.2f, oldest age %.2f
          Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf
          pow-mort Covariance matrix %f iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d)) %f [%f ; %f] First Likeli=%12.6f ipmx=%ld sw=%12.6f %d %8.5fSecond Likeli=%12.6f ipmx=%ld sw=%12.6ftitle=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d ftol=%e stepm=%d ncovcol=%d nlstate=%d ndeath=%d maxwav=%d mle= 0 weight=%d model=%s %d%d %1d%1d %.5e# Covariance matrix # 121 Var(a12) # 122 Cov(b12,a12) Var(b12) # ... # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23) agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d # agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood). agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d begin-prev-date=%lf/%lf/%lf end-prev-date=%lf/%lf/%lf mov_average=%d begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d pop_based=%d prevforecast=%d starting-proj-date=%lf/%lf/%lf final-proj-date=%lf/%lf/%lf mobil_average=%d prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d Problem with stable prevalence resultfile: %s Computing stable prevalence: result on file '%s' #Stable prevalence #Age %d-%d %.5fProblem with Pij resultfile: %s Computing pij: result on file '%s' #****** h Pij x Probability to be in state j at age x+h being in i at x #****** # Cov Agex agex+h hpijx with i,j=%d %3.f %3.fProblem with total LE resultfile: %s Computing Total LEs with variances: file '%s' Problem with Health Exp. resultfile: %s Computing Health Expectancies: result on file '%s' Problem with variance resultfile: %s Computing Variance-covariance of DFLEs: file '%s' #Total LEs with variances: e.. (std) e.%d (std) %4.0f %7.3f (%7.3f)Problem with variance of stable prevalence resultfile: %s Computing Variance-covariance of stable prevalence: file '%s' End of Imach with %d errors and/or %d warnings End of Imach with %d errors and/or warnings %d End of Imach See log file on %s Local time at start %s Localtime at end %sLocal time at start %s Local time at end %s Total time used %s Total time was %d Sec.
          Local time at start %s
          Local time at end %s
          "gnuplot Starting graphs with: %s Problem with gnuplot Wait... 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