title: Linear mixed models with heterogeneous within-cluster variances.
abstract: This paper describes an extension of linear mixed models to allow for heterogeneous within-cluster variances in the analysis of clustered data. Unbiased estimating equations based on quasilikelihood/pseudolikelihood and method of moments are introduced and are shown to give consistent estimators of the regression coefficients, variance components, and heterogeneity parameter under regularity conditions. Cluster-specific random effects and variances are predicted by the posterior modes. The method is illustrated through an analysis of menstrual diary data and its properties are evaluated in a simulation study.
authors.affiliation: Department of Biostatistics, University of Michigan, Ann Arbor 48109, USA.
authors.forename: X
authors.initials: X
authors.lastname: Lin
authors.forename: J
authors.initials: J
authors.lastname: Raz
authors.forename: S D
authors.initials: SD
authors.lastname: Harlow
mesh_terms: D000293:Adolescent; D000328:Adult; D000704:Analysis of Variance; D001699:Biometry / Q000379:methods; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D008499:Medical Records; D008598:Menstruation / Q000502:physiology; D015233:Models, Statistical; D010507:Periodicity