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Re: st: dropping vars from analysis under conditions

From   Maarten Buis <>
Subject   Re: st: dropping vars from analysis under conditions
Date   Tue, 17 Apr 2012 14:09:01 +0200

On Tue, Apr 17, 2012 at 12:35 PM, Nick Cox wrote:
> Expansion by time spent also sounds very dubious. If that means #
> observations for # units of time spent, well, the frequency
> interpretation depends on units of time being discrete, and on which
> units you use, and there is now a cluster structure.

There are situations where this can make sense. This can be used as a
trick to estimate a discrete time survival analysis model or a
sequential logit model. In those cases the total contribution of each
individual to the log-likelihood is the sum of the log-likelihoods of
passing each step/period/transition. It does not matter if we first
sum the contributions of each transition within a person and than sum
over the person (which is what a purpose written program (might) do),
or do the entire sum in one go (which is what you do when you expand).
So, the expansion can be used as a computational trick with which you
can estimate a survival model using programs that are not designed to
estimate a survival model.

Having said all that, using such tricks correctly is tricky. These
programs are not designed for that kind of analysis, and there can
easily be many options and post-estimation commands that will give you
output that does not make sense in this case. One example I can think
of right now is anything that relies on the sample size: e.g. BIC and
AIC values, but there may be (many) more. It is now up to the user to
understand what does and does not make sense. On the other hand Stata
has a whole suit of programs specifically designed for analyzing
survival data, see -help st-. Using these commands seem to me the
safer option.

Hope this helps,

Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
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