Lin X, Raz J, Harlow S D
Department of Biostatistics, University of Michigan, Ann Arbor 48109, USA.
Biometrics. 1997 Sep;53(3):910-23.
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.
本文描述了线性混合模型的一种扩展,以便在聚类数据分析中考虑聚类内的异质方差。引入了基于拟似然/伪似然和矩方法的无偏估计方程,并证明在正则条件下能给出回归系数、方差分量和异质性参数的一致估计量。通过后验模式预测特定聚类的随机效应和方差。通过对月经日记数据的分析来说明该方法,并在模拟研究中评估其性质。