12 0.0 0.0 @@ -485,15 +484,16 @@ prevalences and health expectancies - -Similarly, it is possible to get extrapolated stationary +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 @@ -527,30 +527,47 @@ expectancies
pop_based=0-
The user has the possibility to choose between -population-based or status-based health expectancies. If -pop_based=0 then status-based health expectancies are computed -and if pop_based=1, the programme computes population-based -health expectancies. Health expectancies are weighted averages of -health expectancies respective of the initial state. For a -status-based index, the weights are the cross-sectional -prevalences observed between two dates, as previously -explained, whereas for a population-based index, the weights -are the stationary prevalences.
+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
+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. 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.
+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
@@ -569,12 +586,28 @@ 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
- -Structure of the data file pyram.txt -: age numbers
- -
+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 +
@@ -775,18 +808,18 @@ 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 @@ -813,14 +846,14 @@ href="trbiaspar.txt">-Total life expectancy by @@ -921,16 +954,30 @@ program while saving the old output file
75 487781.02 91367.97 121915.51 74 512892.07 85003.47 117282.76 +- Prevalence forecasting: frbiaspar.txt
-On a d'abord estimé la date moyenne des interviaew. ie -13/9/1995. This file contains
- -Example, at date 1/1/1989 :
- -73 0.807 0.078 0.115
- -This means that at age 73, the probability for a person age 70 -at 13/9/1989 to be in state 1 is 0.807, in state 2 is 0.078 and -to die is 0.115 at 1/1/1989.
+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
@@ -946,9 +993,14 @@ to die is 0.115 at 1/1/1989.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 Enter the parameter fi
- @@ -1138,7 +1190,7 @@ simple justification (name, email, insti href="mailto:brouard@ined.fr">mailto:brouard@ined.fr and mailto:lievre@ined.fr . -IMACH, Version 0.7 Enter +
IMACH, Version 0.71 Enter the parameter file name: ..\mytry\imachpar.txt
Latest version (0.7 of February 2002) can be accessed at Latest version (0.71a of March 2002) can be accessed at http://euroreves.ined.fr/imach