CONDITIONAL LOGISTIC-REGRESSION MODELS FOR CORRELATED BINARY DATA
成果类型：
Article
署名作者：
CONNOLLY, MA; LIANG, KY
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/75.3.501
发表日期：
1988
页码：
501506
关键词：
摘要：
A class of conditional logistic regression models for clustered binary data is considered. This includes the polychotomous logistic model of Rosner (1984) as a special case. Properties such as the joint distribution and pairwise odds ratio are investigated. A class of easily computed estimating functions is introduced which is shown to have high efficiency compared to the computationally intensive maximum likelihood approach. An example on chronic obstructive pulmonary disease among sibs is presented for illustration.