Bayesian model comparison in generalized linear models across multiple groups

被引:1
|
作者
Liao, TFT
机构
[1] Univ Essex, Dept Sociol, Wivenhoe Pk CO4 3SQ, Essex, England
[2] Univ Illinois, Sch Sociol & Stat, Urbana, IL 61801 USA
关键词
generalized linear models; Bayesian statistics; multiple group comparison;
D O I
10.1016/S0167-9473(01)00061-5
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper extends the statistical method known as generalized linear Bayesian modeling developed by Adrian Raftery to the comparison of generalized linear models across multiple groups. The extension considers all relevant hierarchical models in the model space and tests parameter equality across groups by using Bayesian posterior information from the models. The conclusion drawn by using the proposed approach tends to be more conservative than Raftery's method and the conventional likelihood ratio test, as the examples demonstrates. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:311 / 327
页数:17
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