[R] GEE with Inverse Probability Weights

Thomas Lumley tlumley at uw.edu
Thu Jul 5 23:46:26 CEST 2012


If you're going to reply to something from two weeks ago, it's helpful
to include more of the conversation.

However, the mechanism is straightforward.  The standard error
estimator assumes only that observations in different clusters are
independent: it approximates the variance of the estimating functions
by the empirical variance of the cluster totals of the estimating
functions, and uses the delta method to convert this to a variance for
the coefficients.   It's the same as GEE.

In this simple setting it's the same as the GEE variance estimator.

   - thomas



On Fri, Jul 6, 2012 at 7:40 AM, Joshua Wiley <jwiley.psych at gmail.com> wrote:
> Hi Frank,
>
> It clusters by twin, that is why in Dr. Lumley's example, the "id" was
> twin pair, not individual, and the SE is adjusted accordingly.
>
> Cheers,
>
> Josh
>
> On Thu, Jul 5, 2012 at 12:10 PM, RFrank <sparkyjc at gmail.com> wrote:
>> Thanks -- extremely helpful.  But what is the mechanism by which this
>> analysis corrects for the fact that my subjects are clustered (twins)?
>>
>> --
>> View this message in context: http://r.789695.n4.nabble.com/GEE-with-Inverse-Probability-Weights-tp4633172p4635533.html
>> Sent from the R help mailing list archive at Nabble.com.
>>
>> ______________________________________________
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>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
>
>
> --
> Joshua Wiley
> Ph.D. Student, Health Psychology
> Programmer Analyst II, Statistical Consulting Group
> University of California, Los Angeles
> https://joshuawiley.com/
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.



-- 
Thomas Lumley
Professor of Biostatistics
University of Auckland



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