Department of Community Health Sciences, 2129University of Calgary, University of Calgary, Calgary, Canada.
Department of Clinical Neurosciences, 2129University of Calgary, University of Calgary, Calgary, Canada.
Stat Methods Med Res. 2022 Apr;31(4):646-657. doi: 10.1177/09622802211032705. Epub 2021 Dec 13.
Discriminant analysis procedures that assume parsimonious covariance and/or means structures have been proposed for distinguishing between two or more populations in multivariate repeated measures designs. However, these procedures rely on the assumptions of multivariate normality which is not tenable in multivariate repeated measures designs which are characterized by binary, ordinal, or mixed types of response distributions. This study investigates the accuracy of repeated measures discriminant analysis (RMDA) based on the multivariate generalized estimating equations (GEE) framework for classification in multivariate repeated measures designs with the same or different types of responses repeatedly measured over time. Monte Carlo methods were used to compare the accuracy of RMDA procedures based on GEE, and RMDA based on maximum likelihood estimators (MLE) under diverse simulation conditions, which included number of repeated measure occasions, number of responses, sample size, correlation structures, and type of response distribution. RMDA based on GEE exhibited higher average classification accuracy than RMDA based on MLE especially in multivariate non-normal distributions. Three repeatedly measured responses namely severity of epilepsy, current number of anti-epileptic drugs, and parent-reported quality of life in children with epilepsy were used to demonstrate the application of these procedures.
判别分析程序假设简约协方差和/或均值结构，已被提议用于在多元重复测量设计中区分两个或多个群体。然而，这些程序依赖于多元正态性的假设，而多元重复测量设计的特点是二进制、有序或混合类型的响应分布，这是不可行的。本研究调查了基于重复测量判别分析（RMDA）的准确性，该方法基于多元广义估计方程（GEE）框架，用于对具有相同或不同类型响应的多元重复测量设计中的分类，这些响应在时间上重复测量。蒙特卡罗方法用于比较基于 GEE 的 RMDA 程序和基于最大似然估计量（MLE）的 RMDA 程序的准确性，在不同的模拟条件下，包括重复测量次数、响应数量、样本量、相关结构和响应分布类型。基于 GEE 的 RMDA 表现出比基于 MLE 的 RMDA 更高的平均分类准确性，特别是在多元非正态分布中。三个重复测量的响应，即癫痫的严重程度、当前抗癫痫药物的数量和父母报告的癫痫儿童的生活质量，被用来演示这些程序的应用。
