On 3/27/07, [email protected] <[email protected]> wrote:
I heard of inverse probability of treatment weights (IPTW) and would like
to know if I am implementing them correctly on Stata (my data are PANEL).
Is the reference for that:
Little Bird (2007), On the Inverse Probability of Treatment Weights,
Personal Communication.
Or is there a more solid one? Sebastian and Maarten answered the
question of how to code this in Stata, but as for the substantial
questions like whether it is OK that the probabilities are strictly
below than one, you would need to explain why those weights matter and
how they are used in the model. (And yes, there are still chances that
somebody who is observed to have been married might not have been --
say a marriable guy on uninhabitted island :)).
To my understanding (and I am far from being an expert on survival)
-logit- models are effectively implementing something like Cox model
where you don't want to model the baseline parametrically -- which in
the logit world transfers to using dummies for semiparametric
modeling of the time effects.
Note also that Stata wants to have pweights constant within panel, if
you want to use the panel data. So you need to estimate the overall
probability of treatment for the whole panel/individual, rather than
on the observation-by-observation basis. This may or may not
correspond to your vision of how likely one is to get married over
time, but that's a technical restriction with good enough underlying
statistical reasons (the proper use of panel level estimating
equations).
--
Stas Kolenikov
http://stas.kolenikov.name
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