++++++++++++++++++++++++++++++++++++++++++++++++++++++
Date: Tue, 08 Dec 2009 16:20:10 -0700
From: Laura Templeton <[email protected]>
Subject: st: How do I calculate prvalues for specific time points
in my survival analysis?
Hello,
I am using discrete-time survival analysis to inspect the effects
of a
host of background variables on employment state. I have 4 years
of data
which has been broken down into person/month units. Event
completion is
determined at each month with those finding appropriate
employment
dropping from further analysis (using stset command). Depending
on when
a person is dropped from analysis (i.e., event
completion=suitable
employment), I can have up to 48 time points per person.
My question:
I would like to be able to talk about the predicted probability
of white
men, white women, non-white men and non-white women finding
suitable
employment at specific time points (end of year 1, end of year 2,
etc)
and am having trouble with the code.
So far I am successfully able to report the predicted probability
of
finding appropriate employment for each additional month in the
labour
market with this code:
FOR WHITE MEN
prvalue, x(female 0 vismin 0) rest(mean)
FOR WHITE WOMEN
prvalue, x(female 1 vismin 0) rest(mean)
However, what I really want to know is: what is the predicted
probability of being appropriately employed by the end of the
first year
(months==12) or by the end of the 2nd year (months==24) for white
men?
Or white women? etc.
Any tips on how I would incorporate the time element into my
syntax is
most appreciated!
Laura
++++++++++++++++++++++++++++++++++++++++++++++++++++++
I think you need first to clarify in your own mind whether you
want conditional or unconditional probabilities -- e.g. Pr(gets
job in month 12, given no job in months 1 to 11 and
characteristics X), versus unconditional Pr(has job in month 12,
given characteristics X). The former is the discrete time hazard
rate.
Have a look at the Lesson on discrete time survival analysis
associated with my on-line Stata course (URL below signature). It
has examples of how to create discrete time hazard rates,
survival probabilities (and their complement). They involve use
of -predict- after estimation, and then some basic manipulations.
Stephen
-------------------------------------
Professor Stephen P. Jenkins <[email protected]>
Institute for Social and Economic Research (ISER)
University of Essex, Colchester CO4 3SQ, UK
Tel: +44(0)1206 873374. Fax: +44(0)1206 873151
http://www.iser.essex.ac.uk
Survival Analysis using Stata:
http://www.iser.essex.ac.uk/iser/teaching/module-ec968
Downloadable papers and software:
http://ideas.repec.org/e/pje7.html
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