Intra-class correlation in random-effects models for binary data

We review the concept of intra-class correlation in random-effects models for binary outcomes as estimated by Stata’s xtprobit, xtlogit, and xtclog. We consider the usual measures of correlation based on a latent variable formulation of these models and note corrections to the last two procedures. We also discuss alternative measures of association based on manifest variables or actual outcomes and introduce a new command xtrho for computing these measures for all three types of models.


Issue Date:
2002
Publication Type:
Journal Article
DOI and Other Identifiers:
st0031 (Other)
PURL Identifier:
http://purl.umn.edu/116030
Published in:
Stata Journal, Volume 03, Number 1
Page range:
32-46
Total Pages:
15

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 Record created 2017-04-01, last modified 2017-08-26

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