--- imach096d/doc/imach.htm 2001/03/14 08:24:41 1.2 +++ imach096d/doc/imach.htm 2001/05/09 14:09:37 1.3 @@ -28,8 +28,8 @@ src="euroreves2.gif" width="151" height= color="#00006A">INED and EUROREVES -

March -2000

+

Version +64b, May 2001


@@ -273,7 +273,7 @@ weights or covariates, you must fill the

Your first example parameter file

-

#Imach version 0.63, February 2000, +

#Imach version 0.64b, May 2001, INED-EUROREVES

This is a comment. Comments start with a '#'.

@@ -365,6 +365,8 @@ Additional covariates can be included wi
  • if model=V1*V2 the model includes the product of the first and the second covariate (fields 2 and 3)
  • +
  • if model=V1+V1*age the model includes + the product covariate*age
  • Guess values for optimization

    Once the optimization is finished, some graphics can be made with a grapher. We use Gnuplot which is an interactive plotting -program copyrighted but freely distributed. Imach outputs the -source of a gnuplot file, named 'graph.gp', which can be directly -input into gnuplot.
    +program copyrighted but freely distributed. A gnuplot reference +manual is available here.
    When the running is finished, the user should enter a caracter for plotting and output editing.

    @@ -543,16 +544,8 @@ for plotting and output editing.

    @@ -578,9 +571,6 @@ The header of the file is

    71 0.99681 625 627 71 0.00319 2 627 72 0.97125 1115 1148 72 0.02875 33 1148 -
    # Age Prev(1) N(1) N Age Prev(2) N(2) N
    -    70 0.95721 604 631 70 0.04279 27 631
    -

    It means that at age 70, the prevalence in state 1 is 1.000 and in state 2 is 0.00 . At age 71 the number of individuals in state 1 is 625 and in state 2 is 2, hence the total number of @@ -592,22 +582,26 @@ covariance matrix: This file contains all the maximisation results:

    -
     Number of iterations=47
    - -2 log likelihood=46553.005854373667  
    - Estimated parameters: a12 = -12.691743 b12 = 0.095819 
    -                       a13 = -7.815392   b13 = 0.031851 
    -                       a21 = -1.809895 b21 = -0.030470 
    -                       a23 = -7.838248  b23 = 0.039490  
    - Covariance matrix: Var(a12) = 1.03611e-001
    -                    Var(b12) = 1.51173e-005
    -                    Var(a13) = 1.08952e-001
    -                    Var(b13) = 1.68520e-005  
    -                    Var(a21) = 4.82801e-001
    -                    Var(b21) = 6.86392e-005
    -                    Var(a23) = 2.27587e-001
    -                    Var(b23) = 3.04465e-005 
    +
     -2 log likelihood= 21660.918613445392
    + Estimated parameters: a12 = -12.290174 b12 = 0.092161 
    +                       a13 = -9.155590  b13 = 0.046627 
    +                       a21 = -2.629849  b21 = -0.022030 
    +                       a23 = -7.958519  b23 = 0.042614  
    + Covariance matrix: Var(a12) = 1.47453e-001
    +                    Var(b12) = 2.18676e-005
    +                    Var(a13) = 2.09715e-001
    +                    Var(b13) = 3.28937e-005  
    +                    Var(a21) = 9.19832e-001
    +                    Var(b21) = 1.29229e-004
    +                    Var(a23) = 4.48405e-001
    +                    Var(b23) = 5.85631e-005 
      
    +

    By substitution of these parameters in the regression model, +we obtain the elementary transition probabilities:

    + +

    +
    - Transition probabilities: pijrbiaspar.txt
    @@ -617,30 +611,33 @@ is a multiple of 2 years. The first colu the transition probabilities p11, p12, p13, p21, p22, p23. For example, line 5 of the file is:

    -
     100 106 0.03286 0.23512 0.73202 0.02330 0.19210 0.78460 
    +
     100 106 0.02655 0.17622 0.79722 0.01809 0.13678 0.84513 

    and this means:

    -
    p11(100,106)=0.03286
    -p12(100,106)=0.23512
    -p13(100,106)=0.73202
    -p21(100,106)=0.02330
    -p22(100,106)=0.19210 
    -p22(100,106)=0.78460 
    +
    p11(100,106)=0.02655
    +p12(100,106)=0.17622
    +p13(100,106)=0.79722
    +p21(100,106)=0.01809
    +p22(100,106)=0.13678
    +p22(100,106)=0.84513 
    - Stationary prevalence in each state: plrbiaspar.txt
    -
    #Age 1-1 2-2 
    -70 0.92274 0.07726 
    -71 0.91420 0.08580 
    -72 0.90481 0.09519 
    -73 0.89453 0.10547
    +
    #Prevalence
    +#Age 1-1 2-2
    +
    +#************ 
    +70 0.90134 0.09866
    +71 0.89177 0.10823 
    +72 0.88139 0.11861 
    +73 0.87015 0.12985 
    -

    At age 70 the stationary prevalence is 0.92274 in state 1 and -0.07726 in state 2. This stationary prevalence differs from +

    At age 70 the stationary prevalence is 0.90134 in state 1 and +0.09866 in state 2. This stationary prevalence differs from observed prevalence. Here is the point. The observed prevalence at age 70 results from the incidence of disability, incidence of recovery and mortality which occurred in the past of the cohort. @@ -664,24 +661,24 @@ design of the survey, and, for the stati model used and fitted. It is possible to compute the standard deviation of the stationary prevalence at each age.

    -
    Observed and stationary +
    -Observed and stationary prevalence in state (2=disable) with the confident interval: -vbiaspar2.gif
    +vbiaspar21.gif
    -


    -This graph exhibits the stationary prevalence in state (2) with -the confidence interval in red. The green curve is the observed -prevalence (or proportion of individuals in state (2)). Without -discussing the results (it is not the purpose here), we observe -that the green curve is rather below the stationary prevalence. -It suggests an increase of the disability prevalence in the -future.

    - -

    - -
    Convergence to the -stationary prevalence of disability: pbiaspar1.gif
    -
    +

    This graph exhibits the stationary prevalence in state (2) +with the confidence interval in red. The green curve is the +observed prevalence (or proportion of individuals in state (2)). +Without discussing the results (it is not the purpose here), we +observe that the green curve is rather below the stationary +prevalence. It suggests an increase of the disability prevalence +in the future.

    + +

    + +
    -Convergence to the +stationary prevalence of disability: pbiaspar11.gif
    +

    This graph plots the conditional transition probabilities from an initial state (1=healthy in red at the bottom, or 2=disable in @@ -703,23 +700,23 @@ href="erbiaspar.txt">erbiaspar.txt# Health expectancies # Age 1-1 1-2 2-1 2-2 -70 10.7297 2.7809 6.3440 5.9813 -71 10.3078 2.8233 5.9295 5.9959 -72 9.8927 2.8643 5.5305 6.0033 -73 9.4848 2.9036 5.1474 6.0035

    +70 10.9226 3.0401 5.6488 6.2122 +71 10.4384 3.0461 5.2477 6.1599 +72 9.9667 3.0502 4.8663 6.1025 +73 9.5077 3.0524 4.5044 6.0401 -
    For example 70 10.7297 2.7809 6.3440 5.9813 means:
    -e11=10.7297 e12=2.7809 e21=6.3440 e22=5.9813
    +
    For example 70 10.9226 3.0401 5.6488 6.2122 means:
    +e11=10.9226 e12=3.0401 e21=5.6488 e22=6.2122
    -
    +

    For example, life expectancy of a healthy individual at age 70 -is 10.73 in the healthy state and 2.78 in the disability state -(=13.51 years). If he was disable at age 70, his life expectancy -will be shorter, 6.34 in the healthy state and 5.98 in the -disability state (=12.32 years). The total life expectancy is a -weighted mean of both, 13.51 and 12.32; weight is the proportion +is 10.92 in the healthy state and 3.04 in the disability state +(=13.96 years). If he was disable at age 70, his life expectancy +will be shorter, 5.64 in the healthy state and 6.21 in the +disability state (=11.85 years). The total life expectancy is a +weighted mean of both, 13.96 and 11.85; weight is the proportion of people disabled at age 70. In order to get a pure period index (i.e. based only on incidences) we use the computed or @@ -736,7 +733,7 @@ href="vrbiaspar.txt">vrbiaspar.txtFor example, the covariances of life expectancies Cov(ei,ej) at age 50 are (line 3)

    -
       Cov(e1,e1)=0.4667  Cov(e1,e2)=0.0605=Cov(e2,e1)  Cov(e2,e2)=0.0183
    +
       Cov(e1,e1)=0.4776  Cov(e1,e2)=0.0488=Cov(e2,e1)  Cov(e2,e2)=0.0424
    - Health @@ -746,24 +743,24 @@ href="trbiaspar.txt">Total life expectancy by +
    -Total life expectancy by age and health expectancies in states (1=healthy) and (2=disable): -ebiaspar.gif
    +
    ebiaspar1.gif

    This figure represents the health expectancies and the total life expectancy with the confident interval in dashed curve.

    -
            
    +
            

    Standard deviations (obtained from the information matrix of the model) of these quantities are very useful. @@ -826,9 +823,7 @@ estimated by month on 8,000 people may t Also, the program is not yet a statistical package, which permits a simple writing of the variables and the model to take into account in the maximisation. The actual program allows only to -add simple variables without covariations, like age+sex but -without age+sex+ age*sex . This can be done from the source code -(you have to change three lines in the source code) but will +add simple variables like age+sex or age+sex+ age*sex but will never be general enough. But what is to remember, is that incidences or probability of change from one state to another is affected by the variables specified into the model.

    @@ -859,21 +854,20 @@ program while saving the old output file

    Since you know how to run the program, it is time to test it on your own computer. Try for example on a parameter file named imachpar.txt which is a -copy of mypar.txt -included in the subdirectory of imach, mytry. Edit it to change the name of -the data file to ..\data\mydata.txt -if you don't want to copy it on the same directory. The file mydata.txt is a smaller file of 3,000 -people but still with 4 waves.

    +href="..\mytry\imachpar.txt">imachpar.txt which is a copy of mypar.txt included in the +subdirectory of imach, mytry. +Edit it to change the name of the data file to ..\data\mydata.txt if you don't want to +copy it on the same directory. The file mydata.txt +is a smaller file of 3,000 people but still with 4 waves.

    Click on the imach.exe icon to open a window. Answer to the question:'Enter the parameter file name:'

    - @@ -983,23 +977,19 @@ requires a caracter:

    IMACH, Version 0.63

    Enter +

    IMACH, Version 0.64b

    Enter the parameter file name: ..\mytry\imachpar.txt

    - +
    Type g for plotting (available - if mle=1), e to edit output files, c to start again,

    and - q for exiting:

    -
    Type e to edit output files, c + to start again, and q for exiting:
    -

    First you should enter g to -make the figures and then you can edit all the results by typing e. -

    +

    First you should enter e to +edit the master file mypar.htm.

    @@ -1043,7 +1037,7 @@ simple justification (name, email, insti href="mailto:brouard@ined.fr">mailto:brouard@ined.fr and mailto:lievre@ined.fr .

    -

    Latest version (0.63 of 16 march 2000) can be accessed at Latest version (0.64b of may 2001) can be accessed at http://euroreves.ined.fr/imach