Selecting the best linear mixed model under REML

被引：127

作者：

Gurka, MJ ^{[1
]}

机构：

[1] Univ Virginia, Sch Med, Div Biostat & Epidemiol, Dept Publ Hlth Sci, Charlottesville, VA 22908 USA

来源：

AMERICAN STATISTICIAN | 2006年 / 60卷 / 01期

关键词：

information criteria; longitudinal data; model selection; random effects; restricted likelihood;

D O I：

10.1198/000313006X90396

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Restricted maximum likelihood (REML) estimation of the parameters of the mixed model has become commonplace, even becoming the default option in many statistical software packages. However, a review of the literature indicates a need to update and clarify model selection techniques under REML, as ambiguities exist on the appropriateness of existing information criteria in this setting. A simulation study as well as an application assisted in gaining an understanding of the performance of information criteria in selecting the best model when using REML estimation.

引用

页码：19 / 26

页数：8

共 15 条

[1] NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION [J].