- ...Methods
- Prepared by Eric Hauet at Institut
National d'Etudes Démographiques, France. This practical guide can
be read in hypertext on the EURO-REVES Web server at the following
URL: http:/euroreves.ined.fr/euroreves/cookdef/cookdef.html
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

- ...table
- A classical form of the life
table is the complete life table. Complete life tables are based on
deaths registered each year. For each age group (single age year) the
number of deaths is determined and is then divided by the
corresponding population size at the middle of the year to obtain an
age-specific death rate. Proportion of those alive at age
*x*dying in the interval [*x*,*x*+1[ is derived. These proportions (probabilities) are the basic quantities from which all*li*(*i*>0) and*Li*are computed. The estimate of the life expectancy at every age*x*,*ex*, is also provided by such a table.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

- ...table
- An abridged life table is like a
complete life table but deals with age intervals greater than one
year, except the first years of life. A typical set of intervals is
[0,1[, [1,5[, [5,10[, [10,15[, etc.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

- ...states
- The distinguishing characteristic of a Markov
process is that it is `memoryless', meaning that the state an
individual occupies next depends on the state currently occupied,
but not on those occupied in the past
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

- ...large
- Those who become ill get well again
quickly.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

- ...comparisons
- In the particular
case of dementia, see for example [11]
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

- ...by[7]
- Validity of these formulae
is conditional to several hypotheses approximately verified when using
life table data and when prevalence ratios are not smoothed.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

- ...interval
- Generally, we have no information about the
distribution of deaths inside the interval. So, we
take
67#20

which is assuming that deaths are uniformly distributed in interval .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

- ...smaller
- This
approximation would be irrelevant if the the sample size of the survey
is very large. In that case, let
the number of death registered during a year, one can use the
formula (see [4] p163):
. But in that case, it is necessary to notice that the approximation of section 3.2.2 (a) deserves also to be removed.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

- ...survey
- If the sample is stratified or has required a important
reweighting on individuals responding because of loss of follow up from the
initial sampling until the health interview, and resampling, then it
can be appropriate to use a more complex formula (which is often provided
from the people doing the sampling).
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

- ...negligible
- The following general
formulae (for example, see [10] chapter 13) must be used
(
*X*and*Y*are assumed as random variables) and applied to formula 8:80#26

where is

*E*(*X*) and is*E*(*Y*). Moreover, if*X*and*Y*are two ratios measured on the same age-group*i*,.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

- ...expectancies
- It is the same for
the difference between Life expectancy and Health expectancy.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Fri Apr 25 22:40:35 DFT 1997