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Re: st: random-intercept model & variation in time spacing and number of measurements


From   Steve Samuels <[email protected]>
To   [email protected]
Subject   Re: st: random-intercept model & variation in time spacing and number of measurements
Date   Thu, 1 Aug 2013 18:09:40 -0400

This type of model will be appropriate if time and, possibly, polynomial
terms in time, are among the covariates. But -xtlogit- has limited
capabilities for random effects. Use instead -meqrlogit- or, for Stata
<13, -xtmelogit-. These commands will fit a far richer set of models, that
can include, for example, random slopes and nonconstant standard
deviations.

Steve

On Aug 1, 2013, at 2:06 PM, Caroline Wilson wrote:

Hi everyone,

I'm running a random-intercept logistic regression model on a longitudinal dataset using xtlogit. Could someone please tell me whether this type of model is appropriate for data structures where the number of measurements and their time spacing varies across people in the dataset?

Many thanks!
Carrie 		 	   		  
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