title: Generalized variance component models for clustered categorical response variables.
abstract: A generalized variance component model is proposed for the analysis of a categorical response variable with extra-multinomial variation. Categorical data obtained from research designs such as randomized multicenter clinical trials or complex sample surveys with clustering frequently exhibit extra-variation resulting from intracluster correlation. General correlation patterns are accounted for by utilizing a mixed-effects modelling approach, estimating the cluster variance components through the method of moments and modelling functions of the observed proportions through the use of estimating equations. A flexible set of assumptions characterizing the underlying covariance structure for the proportions can be accommodated. The importance of accounting for extra-variation when performing hypothesis tests is highlighted with an application to data from a multi-investigator clinical trial.
authors.affiliation: Division of Biostatistics, Indiana University Department of Medicine, Indianapolis 46202-5200.
authors.forename: M E
authors.initials: ME
authors.lastname: Miller
authors.forename: J R
authors.initials: JR
authors.lastname: Landis
mesh_terms: D000704:Analysis of Variance; D001699:Biometry; D016000:Cluster Analysis; D006801:Humans; D015233:Models, Statistical; D013812:Therapeutics