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st: Population averaged vs random effects logit


From   Jack Needleman <needlema@ucla.edu>
To   statalist@hsphsun2.harvard.edu
Subject   st: Population averaged vs random effects logit
Date   Fri, 24 Jul 2009 02:56:42 -0700

We have a data set of hospital discharges with 280,000 discharges from a 3-year pooled sample of hospitals. There are 1181 hospitals in the sample, and 1574 hospital-years of data. 841 hospitals are in the sample for only 1 year, 287 for two and, 53 for three years.

We are analyzing a mixed model with a substantial block of patient variables, 10 hospital-level variables that are the focus of the research, and year dummies. For most of the sample, as noted above, there is only a single set of hospital-level variables.

I would have assumed that the correct model was a random effects logit, but in reviewing the literature came across two articles that argue that if you only have a single set of observations at the cluster level, the population averaged model is more appropriate:

Neuhaus JM. Statistical methods for longitudinal and clustered designs with binary responses. Stat Methods Med Res. 1992;1(3):249-73. Review.

Young ML, Preisser JS, Qaqish BF, Wolfson M. Comparison of subject-specific and population averaged models for count data from cluster-unit intervention trials. Stat Methods Med Res. 2007 Apr;16(2):167-84.

The results from the RE model are substantially closer to zero. The purpose of the research is to explore the association of one of the hospital level variables (staffing) on patient outcomes. I would welcome any thoughts from the list members on which model should be preferred. Many thanks.

--
Jack Needleman, PhD
Department of Health Services
UCLA School of Public Health


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