Within- and between-cluster effects in generalized linear mixed models: A discussion of approaches and the xthybrid command
Reinhard Schunck
GESIS–Leibniz–Institute for the Social Sciences
Cologne, Germany
[email protected]
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Francisco Perales
Institute for Social Science Research
University of Queensland
Brisbane, Australia
[email protected]
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Abstract. One typically analyzes clustered data using random- or fixed-effects models.
Fixed-effects models allow consistent estimation of the effects of level-one
variables, even if there is unobserved heterogeneity at level two. However,
these models cannot estimate the effects of level-two variables. Hybrid and
correlated random-effects models are flexible modeling specifications that
separate within- and between-cluster effects and allow for both consistent
estimation of level-one effects and inclusion of level-two variables. In this
article, we elaborate on the separation of within- and between-cluster
effects in generalized linear mixed models. These models present a unifying
framework for an entire class of models whose response variables follow a
distribution from the exponential family (for example, linear, logit, probit,
ordered probit and logit, Poisson, and negative binomial models). We introduce
the user-written command xthybrid, a shell for the meglm command.
xthybrid can fit a variety of hybrid and correlated random-effects
models.
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Reinhard Schunck, Francisco Perales
View all articles with these keywords:
xthybrid, correlated random effects, fixed effects, generalized linear mixed models, hybrid model, meglm, Mundlak model, random effects
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