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一种用于分类数据的混合效应模型。

A mixed-effects model for categorical data.

作者信息

Beitler P J, Landis J R

出版信息

Biometrics. 1985 Dec;41(4):991-1000.

PMID:3830263
Abstract

A mixed model for categorical data from unbalanced designs which is directly analogous to a two-way ANOVA model for quantitative data is proposed. An extension of the fitting constants method is developed to estimate model variance components based on appropriate reductions in sums of squares. The resulting variance component estimators are incorporated into the covariance structure of a general linear models Wald statistic to test for treatment differences. These procedures are illustrated with data obtained from a multicenter clinical trial in which the treatments are regarded as fixed effects and the clinics are regarded as random effects.

摘要

提出了一种用于不平衡设计的分类数据的混合模型,该模型与用于定量数据的双向方差分析模型直接类似。开发了拟合常数方法的扩展,以基于平方和的适当缩减来估计模型方差分量。所得的方差分量估计值被纳入一般线性模型Wald统计量的协方差结构中,以检验治疗差异。这些程序通过从多中心临床试验获得的数据进行说明,其中治疗被视为固定效应,而诊所被视为随机效应。

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