Intra–class correlation in random–effects models for binary data
Abstract. 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.
View all articles by these authors:
Germán Rodríguez, Irma Elo
View all articles with these keywords:
intra-class correlation, random-effects, probit, logit, complementary log-log, Pearson's r, Yule's Q
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