Journal
BIOMETRICAL JOURNAL
Volume 58, Issue 4, Pages 852-867Publisher
WILEY
DOI: 10.1002/bimj.201500093
Keywords
Generalized linear mixed model; ICC; Overdispersion; Poisson distribution; Weibull distribution
Funding
- IAP research Network of the Belgian Government (Belgian Science Policy) [P7/06]
- CNPq, National Council for Scientific and Technological Development, Brazilian science funding agency
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The intraclass correlation is commonly used with clustered data. It is often estimated based on fitting a model to hierarchical data and it leads, in turn, to several concepts such as reliability, heritability, inter-rater agreement, etc. For data where linear models can be used, such measures can be defined as ratios of variance components. Matters are more difficult for non-Gaussian outcomes. The focus here is on count and time-to-event outcomes where so-called combined models are used, extending generalized linear mixed models, to describe the data. These models combine normal and gamma random effects to allow for both correlation due to data hierarchies as well as for overdispersion. Furthermore, because the models admit closed-form expressions for the means, variances, higher moments, and even the joint marginal distribution, it is demonstrated that closed forms of intraclass correlations exist. The proposed methodology is illustrated using data from agricultural and livestock studies.
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