# Scales (for hessian or gradient estimation) +
- If mle=1 you can enter zeros: +
- If mle=0 you must enter a covariance matrix (usually obtained from an earlier run).
- -# Scales (for hessian or gradient estimation) 12 0. 0. 13 0. 0. 21 0. 0. 23 0. 0.
Covariance matrix of parameters
This is an output if mle=1. But it can be -used as an input to get the vairous output data files (Health +used as an input to get the various output data files (Health expectancies, stationary prevalence etc.) and figures without -rerunning the rather long maximisation phase (mle=0).
- -Each line starts with indices "ijk" followed by the -covariances between aij and bij:
- +rerunning the rather long maximisation phase (mle=0).+Each line starts with indices "ijk" followed by the +covariances between aij and bij:
121 Var(a12)
122 Cov(b12,a12) Var(b12)
...
232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)
-
- If mle=1 you can enter zeros. -
- -# Covariance matrix 121 0. 122 0. 0. @@ -469,32 +517,28 @@ covariances between aij and bij: 212 0. 0. 0. 0. 0. 0. 231 0. 0. 0. 0. 0. 0. 0. 232 0. 0. 0. 0. 0. 0. 0. 0.-
- If mle=0 you must enter a covariance matrix (usually
- obtained from an earlier run).
-
+ obtained from an earlier run).
last -uncommented line
+Age range for calculation of stationary +prevalences and health expectancies
agemin=70 agemax=100 bage=50 fage=100-
Once we obtained the estimated parameters, the program is able
+
Once we obtained the estimated parameters, the program is able
to calculated stationary prevalence, transitions probabilities
-and life expectancies at any age. Choice of age ranges is useful
+and life expectancies at any age. Choice of age range is useful
for extrapolation. In our data file, ages varies from age 70 to
-102. Setting bage=50 and fage=100, makes the program computing
-life expectancy from age bage to age fage. As we use a model, we
-can compute life expectancy on a wider age range than the age
-range from the data. But the model can be rather wrong on big
-intervals.
Similarly, it is possible to get extrapolated stationary -prevalence by age raning from agemin to agemax.
+102. It is possible to get extrapolated stationary prevalence by +age ranging from agemin to agemax. +Setting bage=50 (begin age) and fage=100 (final age), makes +the program computing life expectancy from age 'bage' to age +'fage'. As we use a model, we can interessingly compute life +expectancy on a wider age range than the age range from the data. +But the model can be rather wrong on much larger intervals. +Program is limited to around 120 for upper age!
- agemin= Minimum age for calculation of the stationary prevalence @@ -502,31 +546,139 @@ prevalence by age raning from agemin to stationary prevalence
- bage= Minimum age for calculation of the health expectancies -
- fage= Maximum ages for calculation of the health +
- fage= Maximum age for calculation of the health expectancies
Computing the observed prevalence
+ +begin-prev-date=1/1/1984 end-prev-date=1/6/1988+ +
Statements 'begin-prev-date' and 'end-prev-date' allow to +select the period in which we calculate the observed prevalences +in each state. In this example, the prevalences are calculated on +data survey collected between 1 january 1984 and 1 june 1988. +
-
+
- begin-prev-date= Starting date + (day/month/year) +
- end-prev-date= Final date + (day/month/year) +
Population- or status-based health +expectancies
+ +pop_based=0+ +
The program computes status-based health expectancies, i.e
+health expectancies which depends on your initial health state.
+If you are healthy your healthy life expectancy (e11) is higher
+than if you were disabled (e21, with e11 > e21).
+To compute a healthy life expectancy independant of the initial
+status we have to weight e11 and e21 according to the probability
+to be in each state at initial age or, with other word, according
+to the proportion of people in each state.
+We prefer computing a 'pure' period healthy life expectancy based
+only on the transtion forces. Then the weights are simply the
+stationnary prevalences or 'implied' prevalences at the initial
+age.
+Some other people would like to use the cross-sectional
+prevalences (the "Sullivan prevalences") observed at
+the initial age during a period of time defined
+just above.
+
+
-
+
- popbased= 0 Health expectancies are + computed at each age from stationary prevalences + 'expected' at this initial age. +
- popbased= 1 Health expectancies are + computed at each age from cross-sectional 'observed' + prevalence at this initial age. As all the population is + not observed at the same exact date we define a short + period were the observed prevalence is computed. +
Prevalence forecasting ( Experimental)
+ +starting-proj-date=1/1/1989 final-proj-date=1/1/1992 mov_average=0+ +
Prevalence and population projections are only available if
+the interpolation unit is a month, i.e. stepm=1 and if there are
+no covariate. The programme estimates the prevalence in each
+state at a precise date expressed in day/month/year. The
+programme computes one forecasted prevalence a year from a
+starting date (1 january of 1989 in this example) to a final date
+(1 january 1992). The statement mov_average allows to compute
+smoothed forecasted prevalences with a five-age moving average
+centered at the mid-age of the five-age period.
+
+
-
+
- starting-proj-date= starting date + (day/month/year) of forecasting +
- final-proj-date= final date + (day/month/year) of forecasting +
- mov_average= smoothing with a five-age + moving average centered at the mid-age of the five-age + period. The command mov_average takes + value 1 if the prevalences are smoothed and 0 otherwise. +
Last uncommented line : Population +forecasting
+ +popforecast=0 popfile=pyram.txt popfiledate=1/1/1989 last-popfiledate=1/1/1992+ +
This command is available if the interpolation unit is a
+month, i.e. stepm=1 and if popforecast=1. From a data file
+including age and number of persons alive at the precise date
+‘popfiledate’, you can forecast the number of persons
+in each state until date ‘last-popfiledate’. In this
+example, the popfile pyram.txt
+includes real data which are the Japanese population in 1989.
+
+
-
+
- popforecast= + 0 Option for population forecasting. If + popforecast=1, the programme does the forecasting. +
- popfile= + name of the population file +
- popfiledate= + date of the population population +
- last-popfiledate= + date of the last population projection +
Running Imach with this example
-We assume that you entered your 1st_example
-parameter file as explained above. To
-run the program you should click on the imach.exe icon and enter
+We assume that you typed in your 1st_example
+parameter file as explained above.
+
To run the program you should either:
+
- click on the imach.exe icon and enter
the name of the parameter file which is for example C:\usr\imach\mle\biaspar.txt
-(you also can click on the biaspar.txt icon located in
-C:\usr\imach\mle and put it with -the mouse on the imach window).
- +href="C:\usr\imach\mle\biaspar.imach">C:\usr\imach\mle\biaspar.imach + - You also can locate the biaspar.imach icon in +C:\usr\imach\mle with your mouse and drag it with +the mouse on the imach window). +
- With latest version (0.7 and higher) if you setup windows in order to +understand ".imach" extension you can right click the +biaspar.imach icon and either edit with notepad the parameter file or +execute it with imach or whatever. +
The time to converge depends on the step unit that you used (1 +The time to converge depends on the step unit that you used (1 month is cpu consuming), on the number of cases, and on the -number of variables.
+number of variables. -The program outputs many files. Most of them are files which -will be plotted for better understanding.
+The program outputs many files. Most of them are files which +will be plotted for better understanding.
@@ -536,11 +688,11 @@ and graphs
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. A gnuplot reference
-manual is available here.
+manual is available here.
When the running is finished, the user should enter a caracter
-for plotting and output editing.
These caracters are:
+These caracters are:
- 'c' to start again the program from the beginning. @@ -578,7 +730,7 @@ people aged 71 is 625+2=627.
- Estimated parameters and -covariance matrix: rbiaspar.txt
+covariance matrix: rbiaspar.imachThis file contains all the maximisation results:
@@ -705,18 +857,18 @@ href="erbiaspar.txt">erbiaspar.txt -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 70 10.4227 3.0402 5.6488 5.7123 means: +e11=10.4227 e12=3.0402 e21=5.6488 e22=5.7123
For example, life expectancy of a healthy individual at age 70 -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 +is 10.42 in the healthy state and 3.04 in the disability state +(=13.46 years). If he was disable at age 70, his life expectancy +will be shorter, 5.64 in the healthy state and 5.71 in the +disability state (=11.35 years). The total life expectancy is a +weighted mean of both, 13.46 and 11.35; 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 @@ -743,14 +895,14 @@ href="trbiaspar.txt">-Total life expectancy by @@ -848,14 +1000,61 @@ file: - Prevalence forecasting: +frbiaspar.txt + +
First, +we have estimated the observed prevalence between 1/1/1984 and +1/6/1988. The mean date of interview (weighed average of the +interviews performed between1/1/1984 and 1/6/1988) is estimated +to be 13/9/1985, as written on the top on the file. Then we +forecast the probability to be in each state.
+ +Example, +at date 1/1/1989 :
+ +# StartingAge FinalAge P.1 P.2 P.3 +# Forecasting at date 1/1/1989 + 73 0.807 0.078 0.115+ +
Since +the minimum age is 70 on the 13/9/1985, the youngest forecasted +age is 73. This means that at age a person aged 70 at 13/9/1989 +has a probability to enter state1 of 0.807 at age 73 on 1/1/1989. +Similarly, the probability to be in state 2 is 0.078 and the +probability to die is 0.115. Then, on the 1/1/1989, the +prevalence of disability at age 73 is estimated to be 0.088.
+ +- Population forecasting: +poprbiaspar.txt
+ +# Age P.1 P.2 P.3 [Population] +# Forecasting at date 1/1/1989 +75 572685.22 83798.08 +74 621296.51 79767.99 +73 645857.70 69320.60+ +
# Forecasting at date 1/1/19909 +76 442986.68 92721.14 120775.48 +75 487781.02 91367.97 121915.51 +74 512892.07 85003.47 117282.76+ +
From the population file, we estimate the number of people in +each state. At age 73, 645857 persons are in state 1 and 69320 +are in state 2. One year latter, 512892 are still in state 1, +85003 are in state 2 and 117282 died before 1/1/1990.
+-
Trying an example
+Trying an example
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
+href="..\mytry\imachpar.imach">imachpar.imach which is a copy of mypar.imach 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
@@ -867,8 +1066,8 @@ question:'Enter the parameter fi
Enter
- the parameter file name: ..\mytry\imachpar.txt Enter
+ the parameter file name: ..\mytry\imachpar.imach This software have been partly granted by mailto:brouard@ined.fr and mailto:lievre@ined.fr . Latest version (0.64b of may 2001) can be accessed at http://euroreves.ined.fr/imach Latest version (0.8 of March 2002) can be accessed at http://euroreves.ined.fr/imach
@@ -886,7 +1085,7 @@ href="imachrun.LOG">this Log file
#
title=MLE datafile=..\data\mydata.txt lastobs=3000 firstpass=1 lastpass=3
-ftol=1.000000e-008 stepm=24 ncov=2 nlstate=2 ndeath=1 maxwav=4 mle=1 weight=0
+ftol=1.000000e-008 stepm=24 ncovcol=2 nlstate=2 ndeath=1 maxwav=4 mle=1 weight=0
-
IMACH, Version 0.64b IMACH, Version 0.8
Total number of individuals= 2965, Agemin = 70.00, Agemax= 100.92
@@ -991,7 +1190,7 @@ edit the master file mypar.htm. <
- Observed prevalence in each state: pmypar.txt
- Estimated parameters and the covariance matrix: rmypar.txt
+ href="..\mytry\rmypar.txt">rmypar.imach
- Stationary prevalence in each state: plrmypar.txt
- Transition probabilities: <
- Health expectancies with their variances: trmypar.txt
- Standard deviation of stationary prevalence: vplrmypar.txt
+ href="..\mytry\vplrmypar.txt">vplrmypar.txt
+ - Prevalences forecasting: frmypar.txt
+ - Population forecasting (if popforecast=1): poprmypar.txt
- -One-step transition
- probabilities
- -Convergence to the
- stationary prevalence
- -Observed and stationary
- prevalence in state (1) with the confident interval
- -Observed and stationary
- prevalence in state (2) with the confident interval
- -Health life
- expectancies by age and initial health state (1)
- -Health life
- expectancies by age and initial health state (2)
- -Total life expectancy by
- age and health expectancies in states (1) and (2).
+ -Convergence to the stationary prevalence
+ -Observed and stationary prevalence in state (1) with the confident interval
+ -Observed and stationary prevalence in state (2) with the confident interval
+ -Health life expectancies by age and initial health state (1)
+ -Health life expectancies by age and initial health state (2)
+ -Total life expectancy by age and health expectancies in states (1) and (2).
+
