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 Coeffucients in Uniform Correlation Models Based on Longitudinal Data

作　　者：范俊花[1,2] 林金官[1] 韦博成[1] 

机构地区：[1]东南大学数学系,南京210096 [2]东南大学成贤学院,南京210088

出　　处：《应用概率统计》2009年第1期12-26,共15页Chinese Journal of Applied Probability and Statistics

基　　金：国家自然科学基金(10671032);江苏省自然科学基金(BK2008284);东南大学科技基金(基地类)资助.

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.In longitudinal data analysis, homogeneity of variance is a basic assumption. However, this assumption is not necessarily appropriate. Lin and Wei 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.

关 键 词：纵向数据 一致相关模型 异方差 相关系数 score检验. 

分 类 号：O212.2[理学—概率论与数理统计]