Conditional Logistic Regression Models for Correlated Binary Data
研究了针对聚类二元数据的条件逻辑回归模型，包括Rosner多项逻辑模型作为特例，探讨了联合分布和配对优势比性质，并引入一类易计算的估计函数，其效率接近计算密集的最大似然法。
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.