Permutation invariance of alternating logistic regression for multivariate binary data
成果类型：
Article
署名作者：
Kuk, AYC
署名单位：
National University of Singapore
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/91.3.758
发表日期：
2004
页码：
758761
关键词：
摘要：
A practically important but not so obvious result is that alternating logistic regression is invariant to permutations of the response variables within clusters. In this note, we give a short proof of the invariance result using a pairwise likelihood argument. The same proof can be used to establish invariance for a more general class of estimating equations based on conditional residuals. As it stands, the invariance theory is incomplete because existing standard error estimates are not invariant to permutations. To solve this problem we present a symmetrised version of the estimating equation and use it to obtain permutation-invariant standard errors.