具有一致相关的纵向数据模型中方差和相关系数的齐性检验

Testing for Homogeneity of Variance and Correlation Coefficients in Uniform Correlation Models Based on Longitudinal Data

摘要: 在纵向数据分析中, 模型方差的齐性是一个基本假定, 但是该假定未必正确. 林金官、韦博成¹讨论了具有AR(1)误差的非线性纵向数据模型中方差和相关系数的齐性检验. 本文对具有一致相关协方差结构的纵向数据模型, 研究了方差齐性和相关系数齐性的检验, 得到了检验的score统计量, 并应用于葡萄糖数据. 最后, 本文还给出了模拟结果.

Abstract: In longitudinal data analysis, homogeneity of variance is a basic assumption. However, this assumption is not necessarily appropriate. Lin and Wei¹ considered the tests for homogeneity of within-individual variances and between-individual autocorrelation coefficients in nonlinear models with AR(1) errors based on longitudinal data. This paper discusses the tests for homogeneity of variances and correlation coefficients in longitudinal data model with uniform correlation covariance structure and obtains several score test statistics. The glucose data is used to illustrate our results. Power simulations of the proposed tests are given in this paper.