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Re: st: Question about multinomial logistic regression and random effects with multiply imputed data


From   Maarten buis <maartenbuis@yahoo.co.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Question about multinomial logistic regression and random effects with multiply imputed data
Date   Tue, 29 Jul 2008 23:04:11 +0100 (BST)

--- Crystal Barksdale <cbarksda@jhsph.edu> wrote:
> I am wondering how (and if) I can do a multinomial random effects
> logistic regression with multiply imputed data. 

Multinomial random effects logistic regression is discussed in (Haan &
Uhlendorf 2006). A nice point of Multiple Imputation is that it is not
method-specific, all it requires is that the sampling distribution of
the parameters is (approximately) Gaussian / normal. As long as this is
(approximately) true, you can use Multiple Imputation for your
multinomial random effects logistic regression. 

There are ofcourse other assumptions like the missing data needs to be
MAR, and if you don't know what that means you'll have to start reading
before you touch -ice- or -mim-. A good starting point is (Allison
2001).

-- Maarten

Allison, P. (2001) Missing Data, Thousand Oaks: Sage.

Haan, P. and Uhlendorf, A. (2006) Estimation of multinomial logit
models with unobserved heterogeneity using maximum simulated
likelihood. The Stata Journal, 6(2): 229--245.

http://www.stata-journal.com/article.html?article=st0104

-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands

visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434

+31 20 5986715

http://home.fsw.vu.nl/m.buis/
-----------------------------------------


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