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<body bgcolor="#FFFFFF">	<body bgcolor="#FFFFFF">
Line 29 color="#00006A">INED</font></a><font col	Line 37 color="#00006A">INED</font></a><font col
href="http://euroreves.ined.fr"><font color="#00006A">EUROREVES</font></a></h3>	href="http://euroreves.ined.fr"><font color="#00006A">EUROREVES</font></a></h3>

<p align="center"><font color="#00006A" size="4"><strong>Version	<p align="center"><font color="#00006A" size="4"><strong>Version
0.7, February 2002</strong></font></p>	0.71a, March 2002</strong></font></p>

<hr size="3" color="#EC5E5E">	<hr size="3" color="#EC5E5E">

Line 58 color="#00006A">) </font></h4>	Line 66 color="#00006A">) </font></h4>

<ul>	<ul>
<li><a href="#intro">Introduction</a> </li>	<li><a href="#intro">Introduction</a> </li>
<li>The detailed statistical model (<a href="docmath.pdf">PDF
version</a>),(<a href="docmath.ps">ps version</a>) </li>
<li><a href="#data">On what kind of data can it be used?</a></li>	<li><a href="#data">On what kind of data can it be used?</a></li>
<li><a href="#datafile">The data file</a> </li>	<li><a href="#datafile">The data file</a> </li>
<li><a href="#biaspar">The parameter file</a> </li>	<li><a href="#biaspar">The parameter file</a> </li>
Line 80 monitor. In low mortality countries, the	Line 86 monitor. In low mortality countries, the
mortality declines, the increase in DFLE is not proportionate to	mortality declines, the increase in DFLE is not proportionate to
the increase in total Life expectancy. This case is called the <em>Expansion	the increase in total Life expectancy. This case is called the <em>Expansion
of morbidity</em>. Most of the data collected today, in	of morbidity</em>. Most of the data collected today, in
particular by the international <a href="http://euroreves/reves">REVES</a>	particular by the international <a href="http://www.reves.org">REVES</a>
network on Health expectancy, and most HE indices based on these	network on Health expectancy, and most HE indices based on these
data, are <em>cross-sectional</em>. It means that the information	data, are <em>cross-sectional</em>. It means that the information
collected comes from a single cross-sectional survey: people from	collected comes from a single cross-sectional survey: people from
Line 273 weights or covariates, you must fill the	Line 279 weights or covariates, you must fill the
<h2><font color="#00006A">Your first example parameter file</font><a	<h2><font color="#00006A">Your first example parameter file</font><a
href="http://euroreves.ined.fr/imach"></a><a name="uio"></a></h2>	href="http://euroreves.ined.fr/imach"></a><a name="uio"></a></h2>

<h2><a name="biaspar"></a>#Imach version 0.7, February 2002,	<h2><a name="biaspar"></a>#Imach version 0.71a, March 2002,
INED-EUROREVES </h2>	INED-EUROREVES </h2>

<p>This is a comment. Comments start with a '#'.</p>	<p>This is a comment. Comments start with a '#'.</p>
Line 321 line</font></a></h4>	Line 327 line</font></a></h4>
<li>... </li>	<li>... </li>
</ul>	</ul>
</li>	</li>
<li><b>ncov=2</b> Number of covariates in the datafile. The	<li><b>ncov=2</b> Number of covariates in the datafile. </li>
intercept and the age parameter are counting for 2
covariates.</li>
<li><b>nlstate=2</b> Number of non-absorbing (alive) states.	<li><b>nlstate=2</b> Number of non-absorbing (alive) states.
Here we have two alive states: disability-free is coded 1	Here we have two alive states: disability-free is coded 1
and disability is coded 2. </li>	and disability is coded 2. </li>
Line 349 line</font></a></h4>	Line 353 line</font></a></h4>
<h4><font color="#FF0000">Covariates</font></h4>	<h4><font color="#FF0000">Covariates</font></h4>

<p>Intercept and age are systematically included in the model.	<p>Intercept and age are systematically included in the model.
Additional covariates can be included with the command </p>	Additional covariates can be included with the command: </p>

<pre>model=<em>list of covariates</em></pre>	<pre>model=<em>list of covariates</em></pre>

Line 369 Additional covariates can be included wi	Line 373 Additional covariates can be included wi
the product covariate*age</li>	the product covariate*age</li>
</ul>	</ul>

	<p>In this example, we have two covariates in the data file
	(fields 2 and 3). The number of covariates is defined with
	statement ncov=2. If now you have 3 covariates in the datafile
	(fields 2, 3 and 4), you have to set ncov=3. Then you can run the
	programme with a new parametrisation taking into account the
	third covariate. For example, <strong>model=V1+V3 </strong>estimates
	a model with the first and third covariates. More complicated
	models can be used, but it will takes more time to converge. With
	a simple model (no covariates), the programme estimates 8
	parameters. Adding covariates increases the number of parameters
	: 12 for <strong>model=V1, </strong>16 for <strong>model=V1+V1*age
	</strong>and 20 for <strong>model=V1+V2+V3.</strong></p>

<h4><font color="#FF0000">Guess values for optimization</font><font	<h4><font color="#FF0000">Guess values for optimization</font><font
color="#00006A"> </font></h4>	color="#00006A"> </font></h4>

Line 398 aij bij</b> </p>	Line 415 aij bij</b> </p>
23 -6.234642 0.022315 </pre>	23 -6.234642 0.022315 </pre>
</blockquote>	</blockquote>

<p>or, to simplify: </p>	<p>or, to simplify (in most of cases it converges but there is no
	warranty!): </p>

<blockquote>	<blockquote>
<pre>12 0.0 0.0	<pre>12 0.0 0.0
Line 407 aij bij</b> </p>	Line 425 aij bij</b> </p>
23 0.0 0.0</pre>	23 0.0 0.0</pre>
</blockquote>	</blockquote>

	<p> In order to speed up the convergence you can make a first run with
	a large stepm i.e stepm=12 or 24 and then decrease the stepm until
	stepm=1 month. If newstepm is the new shorter stepm and stepm can be
	expressed as a multiple of newstepm, like newstepm=n stepm, then the
	following approximation holds:
	<pre>aij(stepm) = aij(n . stepm) - ln(n)
	</pre> and
	<pre>bij(stepm) = bij(n . stepm) .</pre>

	<p> For example if you already ran for a 6 months interval and
	got:<br>
	<pre># Parameters
	12 -13.390179 0.126133
	13 -7.493460 0.048069
	21 0.575975 -0.041322
	23 -4.748678 0.030626
	</pre>
	If you now want to get the monthly estimates, you can guess the aij by
	substracting ln(6)= 1,7917<br> and running<br>
	<pre>12 -15.18193847 0.126133
	13 -9.285219469 0.048069
	21 -1.215784469 -0.041322
	23 -6.540437469 0.030626
	</pre>
	and get<br>
	<pre>12 -15.029768 0.124347
	13 -8.472981 0.036599
	21 -1.472527 -0.038394
	23 -6.553602 0.029856
	</br>
	which is closer to the results. The approximation is probably useful
	only for very small intervals and we don't have enough experience to
	know if you will speed up the convergence or not.
	<pre> -ln(12)= -2.484
	-ln(6/1)=-ln(6)= -1.791
	-ln(3/1)=-ln(3)= -1.0986
	-ln(12/6)=-ln(2)= -0.693
	</pre>

<h4><font color="#FF0000">Guess values for computing variances</font></h4>	<h4><font color="#FF0000">Guess values for computing variances</font></h4>

<p>This is an output if <a href="#mle">mle</a>=1. But it can be	<p>This is an output if <a href="#mle">mle</a>=1. But it can be
Line 420 matrix of the parameters, that is the in	Line 477 matrix of the parameters, that is the in
matrix, and the variances of health expectancies. Each line	matrix, and the variances of health expectancies. Each line
consists in indices "ij" followed by the initial scales	consists in indices "ij" followed by the initial scales
(zero to simplify) associated with aij and bij. </p>	(zero to simplify) associated with aij and bij. </p>
	<ul> <li>If mle=1 you can enter zeros:</li>
<ul>	<blockquote><pre># Scales (for hessian or gradient estimation)
<li>If mle=1 you can enter zeros:</li>
</ul>

<blockquote>
<pre># Scales (for hessian or gradient estimation)
12 0. 0.	12 0. 0.
13 0. 0.	13 0. 0.
21 0. 0.	21 0. 0.
23 0. 0. </pre>	23 0. 0. </pre>
</blockquote>	</blockquote>

<ul>
<li>If mle=0 you must enter a covariance matrix (usually	<li>If mle=0 you must enter a covariance matrix (usually
obtained from an earlier run).</li>	obtained from an earlier run).</li>
</ul>	</ul>
Line 443 consists in indices "ij" follo	Line 493 consists in indices "ij" follo
<p>This is an output if <a href="#mle">mle</a>=1. But it can be	<p>This is an output if <a href="#mle">mle</a>=1. But it can be
used as an input to get the various output data files (Health	used as an input to get the various output data files (Health
expectancies, stationary prevalence etc.) and figures without	expectancies, stationary prevalence etc.) and figures without
rerunning the rather long maximisation phase (mle=0). </p>	rerunning the rather long maximisation phase (mle=0). <br>
	Each line starts with indices "ijk" followed by the
<p>Each line starts with indices "ijk" followed by the	covariances between aij and bij:<br>
covariances between aij and bij: </p>

<pre>	<pre>
121 Var(a12)	121 Var(a12)
122 Cov(b12,a12) Var(b12)	122 Cov(b12,a12) Var(b12)
...	...
232 Cov(b23,a12) Cov(b23,b12) ... Var (b23) </pre>	232 Cov(b23,a12) Cov(b23,b12) ... Var (b23) </pre>

<ul>	<ul>
<li>If mle=1 you can enter zeros. </li>	<li>If mle=1 you can enter zeros. </li>
</ul>

<blockquote>
<pre># Covariance matrix	<pre># Covariance matrix
121 0.	121 0.
122 0. 0.	122 0. 0.
Line 468 covariances between aij and bij: </p>	Line 512 covariances between aij and bij: </p>
212 0. 0. 0. 0. 0. 0.	212 0. 0. 0. 0. 0. 0.
231 0. 0. 0. 0. 0. 0. 0.	231 0. 0. 0. 0. 0. 0. 0.
232 0. 0. 0. 0. 0. 0. 0. 0.</pre>	232 0. 0. 0. 0. 0. 0. 0. 0.</pre>
</blockquote>

<ul>
<li>If mle=0 you must enter a covariance matrix (usually	<li>If mle=0 you must enter a covariance matrix (usually
obtained from an earlier run).<br>	obtained from an earlier run). </li>
</li>
</ul>	</ul>

<h4><font color="#FF0000">Age range for calculation of stationary	<h4><font color="#FF0000">Age range for calculation of stationary
Line 481 prevalences and health expectancies</fon	Line 521 prevalences and health expectancies</fon

<pre>agemin=70 agemax=100 bage=50 fage=100</pre>	<pre>agemin=70 agemax=100 bage=50 fage=100</pre>

<p>Once we obtained the estimated parameters, the program is able	<br>Once we obtained the estimated parameters, the program is able
to calculated stationary prevalence, transitions probabilities	to calculated stationary prevalence, transitions probabilities
and life expectancies at any age. Choice of age range 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	for extrapolation. In our data file, ages varies from age 70 to
102. Setting bage=50 and fage=100, makes the program computing	102. It is possible to get extrapolated stationary prevalence by
life expectancy from age bage to age fage. As we use a model, we	age ranging from agemin to agemax.
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.</p>

<p>Similarly, it is possible to get extrapolated stationary
prevalence by age ranging from agemin to agemax. </p>

	<br>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!
<ul>	<ul>
<li><b>agemin=</b> Minimum age for calculation of the	<li><b>agemin=</b> Minimum age for calculation of the
stationary prevalence </li>	stationary prevalence </li>
Line 510 color="#FF0000"> the observed prevalence	Line 550 color="#FF0000"> the observed prevalence

<pre>begin-prev-date=1/1/1984 end-prev-date=1/6/1988 </pre>	<pre>begin-prev-date=1/1/1984 end-prev-date=1/6/1988 </pre>

<p>Statements 'begin-prev-date' and 'end-prev-date' allow to	<br>Statements 'begin-prev-date' and 'end-prev-date' allow to
select the period in which we calculate the observed prevalences	select the period in which we calculate the observed prevalences
in each state. In this example, the prevalences are calculated on	in each state. In this example, the prevalences are calculated on
data survey collected between 1 january 1984 and 1 june 1988. </p>	data survey collected between 1 january 1984 and 1 june 1988.

<ul>	<ul>
<li><strong>begin-prev-date= </strong>Starting date	<li><strong>begin-prev-date= </strong>Starting date
(day/month/year)</li>	(day/month/year)</li>
Line 527 expectancies</font></h4>	Line 566 expectancies</font></h4>

<pre>pop_based=0</pre>	<pre>pop_based=0</pre>

<p>The user has the possibility to choose between	<p>The program computes status-based health expectancies, i.e
population-based or status-based health expectancies. If	health expectancies which depends on your initial health state.
pop_based=0 then status-based health expectancies are computed	If you are healthy your healthy life expectancy (e11) is higher
and if pop_based=1, the programme computes population-based	than if you were disabled (e21, with e11 > e21).<br>
health expectancies. Health expectancies are weighted averages of	To compute a healthy life expectancy independant of the initial
health expectancies respective of the initial state. For a	status we have to weight e11 and e21 according to the probability
status-based index, the weights are the cross-sectional	to be in each state at initial age or, with other word, according
prevalences observed between two dates, as <a href="#Computing">previously	to the proportion of people in each state.<br>
explained</a>, whereas for a population-based index, the weights	We prefer computing a 'pure' period healthy life expectancy based
are the stationary prevalences.</p>	only on the transtion forces. Then the weights are simply the
	stationnary prevalences or 'implied' prevalences at the initial
	age.<br>
	Some other people would like to use the cross-sectional
	prevalences (the "Sullivan prevalences") observed at
	the initial age during a period of time <a href="#Computing">defined
	just above</a>. <br>

	<ul>
	<li><strong>popbased= 0 </strong>Health expectancies are
	computed at each age from stationary prevalences
	'expected' at this initial age.</li>
	<li><strong>popbased= 1 </strong>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.</li>
	</ul>

<h4><font color="#FF0000">Prevalence forecasting </font></h4>	<h4><font color="#FF0000">Prevalence forecasting ( Experimental)</font></h4>

<pre>starting-proj-date=1/1/1989 final-proj-date=1/1/1992 mov_average=0 </pre>	<pre>starting-proj-date=1/1/1989 final-proj-date=1/1/1992 mov_average=0 </pre>

<p>Prevalence and population projections are only available if	<p>Prevalence and population projections are only available if
the interpolation unit is a month, i.e. stepm=1. The programme	the interpolation unit is a month, i.e. stepm=1 and if there are
estimates the prevalence in each state at a precise date	no covariate. The programme estimates the prevalence in each
expressed in day/month/year. The programme computes one	state at a precise date expressed in day/month/year. The
forecasted prevalence a year from a starting date (1 january of	programme computes one forecasted prevalence a year from a
1989 in this example) to a final date (1 january 1992). The	starting date (1 january of 1989 in this example) to a final date
statement mov_average allows to compute smoothed forecasted	(1 january 1992). The statement mov_average allows to compute
prevalences with a five-age moving average centered at the	smoothed forecasted prevalences with a five-age moving average
mid-age of the five-age period. </p>	centered at the mid-age of the five-age period. <br>

<ul>	<ul>
<li><strong>starting-proj-date</strong>= starting date	<li><strong>starting-proj-date</strong>= starting date
Line 569 forecasting </font></h4>	Line 625 forecasting </font></h4>
<pre>popforecast=0 popfile=pyram.txt popfiledate=1/1/1989 last-popfiledate=1/1/1992</pre>	<pre>popforecast=0 popfile=pyram.txt popfiledate=1/1/1989 last-popfiledate=1/1/1992</pre>

<p>This command is available if the interpolation unit is a	<p>This command is available if the interpolation unit is a
month, i.e. stepm=1 and if popforecast=1. From a data file </p>	month, i.e. stepm=1 and if popforecast=1. From a data file
	including age and number of persons alive at the precise date
<p>Structure of the data file <a href="pyram.txt"><b>pyram.txt</b></a><b>	popfiledate, you can forecast the number of persons
: </b>age numbers</p>	in each state until date last-popfiledate. In this
	example, the popfile <a href="pyram.txt"><b>pyram.txt</b></a>
<p> </p>	includes real data which are the Japanese population in 1989.<br>

	<ul type="disc">
	<li class="MsoNormal"
	style="TEXT-ALIGN: justify; mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; mso-list: l10 level1 lfo36; tab-stops: list 36.0pt"><b>popforecast=
	0 </b>Option for population forecasting. If
	popforecast=1, the programme does the forecasting<b>.</b></li>
	<li class="MsoNormal"
	style="TEXT-ALIGN: justify; mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; mso-list: l10 level1 lfo36; tab-stops: list 36.0pt"><b>popfile=
	</b>name of the population file</li>
	<li class="MsoNormal"
	style="TEXT-ALIGN: justify; mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; mso-list: l10 level1 lfo36; tab-stops: list 36.0pt"><b>popfiledate=</b>
	date of the population population</li>
	<li class="MsoNormal"
	style="TEXT-ALIGN: justify; mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; mso-list: l10 level1 lfo36; tab-stops: list 36.0pt"><b>last-popfiledate</b>=
	date of the last population projection </li>
	</ul>

<hr>	<hr>

<h2><a name="running"></a><font color="#00006A">Running Imach	<h2><a name="running"></a><font color="#00006A">Running Imach
with this example</font></h2>	with this example</font></h2>

<p>We assume that you entered your <a href="biaspar.imach">1st_example	We assume that you typed in your <a href="biaspar.imach">1st_example
parameter file</a> as explained <a href="#biaspar">above</a>. To	parameter file</a> as explained <a href="#biaspar">above</a>.
run the program you should click on the imach.exe icon and enter	<br>To run the program you should either:
	<ul> <li> click on the imach.exe icon and enter
the name of the parameter file which is for example <a	the name of the parameter file which is for example <a
href="C:\usr\imach\mle\biaspar.txt">C:\usr\imach\mle\biaspar.txt</a>	href="C:\usr\imach\mle\biaspar.imach">C:\usr\imach\mle\biaspar.imach</a>
(you also can click on the biaspar.txt icon located in <br>	<li> You also can locate the biaspar.imach icon in
<a href="C:\usr\imach\mle">C:\usr\imach\mle</a> and put it with	<a href="C:\usr\imach\mle">C:\usr\imach\mle</a> with your mouse and drag it with
the mouse on the imach window).<br>	the mouse on the imach window).
</p>	<li> 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.
	</ul>

<p>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	month is cpu consuming), on the number of cases, and on the
number of variables.</p>	number of variables.

<p>The program outputs many files. Most of them are files which	<br>The program outputs many files. Most of them are files which
will be plotted for better understanding.</p>	will be plotted for better understanding.

<hr>	<hr>

Line 608 with a grapher. We use Gnuplot which is	Line 685 with a grapher. We use Gnuplot which is
program copyrighted but freely distributed. A gnuplot reference	program copyrighted but freely distributed. A gnuplot reference
manual is available <a href="http://www.gnuplot.info/">here</a>. <br>	manual is available <a href="http://www.gnuplot.info/">here</a>. <br>
When the running is finished, the user should enter a caracter	When the running is finished, the user should enter a caracter
for plotting and output editing. </p>	for plotting and output editing.

<p>These caracters are:</p>	<br>These caracters are:<br>

<ul>	<ul>
<li>'c' to start again the program from the beginning.</li>	<li>'c' to start again the program from the beginning.</li>
Line 648 people aged 71 is 625+2=627. <br>	Line 725 people aged 71 is 625+2=627. <br>
</p>	</p>

<h5><font color="#EC5E5E" size="3"><b>- Estimated parameters and	<h5><font color="#EC5E5E" size="3"><b>- Estimated parameters and
covariance matrix</b></font><b>: </b><a href="rbiaspar.txt"><b>rbiaspar.txt</b></a></h5>	covariance matrix</b></font><b>: </b><a href="rbiaspar.txt"><b>rbiaspar.imach</b></a></h5>

<p>This file contains all the maximisation results: </p>	<p>This file contains all the maximisation results: </p>

Line 775 href="erbiaspar.txt"><b>erbiaspar.txt</b	Line 852 href="erbiaspar.txt"><b>erbiaspar.txt</b
72 9.9667 3.0502 4.8663 6.1025	72 9.9667 3.0502 4.8663 6.1025
73 9.5077 3.0524 4.5044 6.0401 </pre>	73 9.5077 3.0524 4.5044 6.0401 </pre>

<pre>For example 70 10.9226 3.0401 5.6488 6.2122 means:	<pre>For example 70 10.4227 3.0402 5.6488 5.7123 means:
e11=10.9226 e12=3.0401 e21=5.6488 e22=6.2122</pre>	e11=10.4227 e12=3.0402 e21=5.6488 e22=5.7123</pre>

<pre><img src="expbiaspar21.gif" width="400" height="300"><img	<pre><img src="expbiaspar21.gif" width="400" height="300"><img
src="expbiaspar11.gif" width="400" height="300"></pre>	src="expbiaspar11.gif" width="400" height="300"></pre>

<p>For example, life expectancy of a healthy individual at age 70	<p>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	is 10.42 in the healthy state and 3.04 in the disability state
(=13.96 years). If he was disable at age 70, his life expectancy	(=13.46 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	will be shorter, 5.64 in the healthy state and 5.71 in the
disability state (=11.85 years). The total life expectancy is a	disability state (=11.35 years). The total life expectancy is a
weighted mean of both, 13.96 and 11.85; weight is the proportion	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	of people disabled at age 70. In order to get a pure period index
(i.e. based only on incidences) we use the <a	(i.e. based only on incidences) we use the <a
href="#Stationary prevalence in each state">computed or	href="#Stationary prevalence in each state">computed or
Line 813 href="trbiaspar.txt"><font face="Courier	Line 890 href="trbiaspar.txt"><font face="Courier

<pre>#Total LEs with variances: e.. (std) e.1 (std) e.2 (std) </pre>	<pre>#Total LEs with variances: e.. (std) e.1 (std) e.2 (std) </pre>

<pre>70 13.76 (0.22) 10.40 (0.20) 3.35 (0.14) </pre>	<pre>70 13.26 (0.22) 9.95 (0.20) 3.30 (0.14) </pre>

<p>Thus, at age 70 the total life expectancy, e..=13.76years is	<p>Thus, at age 70 the total life expectancy, e..=13.26 years is
the weighted mean of e1.=13.96 and e2.=11.85 by the stationary	the weighted mean of e1.=13.46 and e2.=11.35 by the stationary
prevalence at age 70 which are 0.90134 in state 1 and 0.09866 in	prevalence at age 70 which are 0.90134 in state 1 and 0.09866 in
state 2, respectively (the sum is equal to one). e.1=10.40 is the	state 2, respectively (the sum is equal to one). e.1=9.95 is the
Disability-free life expectancy at age 70 (it is again a weighted	Disability-free life expectancy at age 70 (it is again a weighted
mean of e11 and e21). e.2=3.35 is also the life expectancy at age	mean of e11 and e21). e.2=3.30 is also the life expectancy at age
70 to be spent in the disability state.</p>	70 to be spent in the disability state.</p>

<h5><font color="#EC5E5E" size="3"><b>-Total life expectancy by	<h5><font color="#EC5E5E" size="3"><b>-Total life expectancy by
Line 921 program while saving the old output file	Line 998 program while saving the old output file
<h5><font color="#EC5E5E" size="3"><b>- Prevalence forecasting</b></font><b>:	<h5><font color="#EC5E5E" size="3"><b>- Prevalence forecasting</b></font><b>:
</b><a href="frbiaspar.txt"><b>frbiaspar.txt</b></a></h5>	</b><a href="frbiaspar.txt"><b>frbiaspar.txt</b></a></h5>

<p>On a d'abord estim� la date moyenne des interviaew. ie	<p
13/9/1995. This file contains </p>	style="TEXT-ALIGN: justify; tab-stops: 45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt">First,
	we have estimated the observed prevalence between 1/1/1984 and
<p>Example, at date 1/1/1989 : </p>	1/6/1988. The mean date of interview (weighed average of the
	interviews performed between1/1/1984 and 1/6/1988) is estimated
<p>73 0.807 0.078 0.115 </p>	to be 13/9/1985, as written on the top on the file. Then we
	forecast the probability to be in each state. </p>
<p>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	<p
to die is 0.115 at 1/1/1989.</p>	style="TEXT-ALIGN: justify; tab-stops: 45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt">Example,
	at date 1/1/1989 : </p>

	<pre class="MsoNormal"># StartingAge FinalAge P.1 P.2 P.3
	# Forecasting at date 1/1/1989
	73 0.807 0.078 0.115</pre>

	<p
	style="TEXT-ALIGN: justify; tab-stops: 45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt">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.</p>

<h5><font color="#EC5E5E" size="3"><b>- Population forecasting</b></font><b>:	<h5><font color="#EC5E5E" size="3"><b>- Population forecasting</b></font><b>:
</b><a href="poprbiaspar.txt"><b>poprbiaspar.txt</b></a></h5>	</b><a href="poprbiaspar.txt"><b>poprbiaspar.txt</b></a></h5>
Line 946 to die is 0.115 at 1/1/1989.</p>	Line 1037 to die is 0.115 at 1/1/1989.</p>
75 487781.02 91367.97 121915.51	75 487781.02 91367.97 121915.51
74 512892.07 85003.47 117282.76 </pre>	74 512892.07 85003.47 117282.76 </pre>

	<p>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.</p>

<hr>	<hr>

<h2><a name="example" </a><font color="#00006A">Trying an example</font></a></h2>	<h2><a name="example"></a><font color="#00006A">Trying an example</font></h2>

<p>Since you know how to run the program, it is time to test it	<p>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 <a	on your own computer. Try for example on a parameter file named <a
href="..\mytry\imachpar.txt">imachpar.txt</a> which is a copy of <font	href="..\mytry\imachpar.imach">imachpar.imach</a> which is a copy of <font
size="2" face="Courier New">mypar.txt</font> included in the	size="2" face="Courier New">mypar.imach</font> included in the
subdirectory of imach, <font size="2" face="Courier New">mytry</font>.	subdirectory of imach, <font size="2" face="Courier New">mytry</font>.
Edit it to change the name of the data file to <font size="2"	Edit it to change the name of the data file to <font size="2"
face="Courier New">..\data\mydata.txt</font> if you don't want to	face="Courier New">..\data\mydata.txt</font> if you don't want to
Line 965 question:'<strong>Enter the parameter fi	Line 1061 question:'<strong>Enter the parameter fi

<table border="1">	<table border="1">
<tr>	<tr>
<td width="100%"><strong>IMACH, Version 0.7</strong><p><strong>Enter	<td width="100%"><strong>IMACH, Version 0.71</strong><p><strong>Enter
the parameter file name: ..\mytry\imachpar.txt</strong></p>	the parameter file name: ..\mytry\imachpar.imach</strong></p>
</td>	</td>
</tr>	</tr>
</table>	</table>
Line 1089 edit the master file mypar.htm. </font><	Line 1185 edit the master file mypar.htm. </font><
- Observed prevalence in each state: <a	- Observed prevalence in each state: <a
href="..\mytry\prmypar.txt">pmypar.txt</a> <br>	href="..\mytry\prmypar.txt">pmypar.txt</a> <br>
- Estimated parameters and the covariance matrix: <a	- Estimated parameters and the covariance matrix: <a
href="..\mytry\rmypar.txt">rmypar.txt</a> <br>	href="..\mytry\rmypar.txt">rmypar.imach</a> <br>
- Stationary prevalence in each state: <a	- Stationary prevalence in each state: <a
href="..\mytry\plrmypar.txt">plrmypar.txt</a> <br>	href="..\mytry\plrmypar.txt">plrmypar.txt</a> <br>
- Transition probabilities: <a	- Transition probabilities: <a
Line 1112 edit the master file mypar.htm. </font><	Line 1208 edit the master file mypar.htm. </font><
</li>	</li>
<li><u>Graphs</u> <br>	<li><u>Graphs</u> <br>
<br>	<br>
-<a href="../mytry/pemypar1.gif">One-step transition	-<a href="../mytry/pemypar1.gif">One-step transition probabilities</a><br>
probabilities</a><br>	-<a href="../mytry/pmypar11.gif">Convergence to the stationary prevalence</a><br>
-<a href="../mytry/pmypar11.gif">Convergence to the	-<a href="..\mytry\vmypar11.gif">Observed and stationary prevalence in state (1) with the confident interval</a> <br>
stationary prevalence</a><br>	-<a href="..\mytry\vmypar21.gif">Observed and stationary prevalence in state (2) with the confident interval</a> <br>
-<a href="..\mytry\vmypar11.gif">Observed and stationary	-<a href="..\mytry\expmypar11.gif">Health life expectancies by age and initial health state (1)</a> <br>
prevalence in state (1) with the confident interval</a> <br>	-<a href="..\mytry\expmypar21.gif">Health life expectancies by age and initial health state (2)</a> <br>
-<a href="..\mytry\vmypar21.gif">Observed and stationary	-<a href="..\mytry\emypar1.gif">Total life expectancy by age and health expectancies in states (1) and (2).</a> </li>
prevalence in state (2) with the confident interval</a> <br>
-<a href="..\mytry\expmypar11.gif">Health life
expectancies by age and initial health state (1)</a> <br>
-<a href="..\mytry\expmypar21.gif">Health life
expectancies by age and initial health state (2)</a> <br>
-<a href="..\mytry\emypar1.gif">Total life expectancy by
age and health expectancies in states (1) and (2).</a> </li>
</ul>	</ul>

<p>This software have been partly granted by <a	<p>This software have been partly granted by <a
Line 1138 simple justification (name, email, insti	Line 1227 simple justification (name, email, insti
href="mailto:brouard@ined.fr">mailto:brouard@ined.fr</a> and <a	href="mailto:brouard@ined.fr">mailto:brouard@ined.fr</a> and <a
href="mailto:lievre@ined.fr">mailto:lievre@ined.fr</a> .</p>	href="mailto:lievre@ined.fr">mailto:lievre@ined.fr</a> .</p>

<p>Latest version (0.7 of February 2002) can be accessed at <a	<p>Latest version (0.71d of March 2002) can be accessed at <a
href="http://euroeves.ined.fr/imach">http://euroreves.ined.fr/imach</a><br>	href="http://euroreves.ined.fr/imach">http://euroreves.ined.fr/imach</a><br>
</p>	</p>
</body>	</body>
</html>	</html>

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