Analysis of Dose-Response Data in the Presence of Extrabinomial Variation
研究了当二元剂量反应数据因自然分组（如窝）而产生额外二项变异时，如何用广义Wald和得分统计量来增强基于二项似然的标准推断方法的稳健性，并以小鼠二恶英致畸实验的probit分析为例。
Binary dose-response data often exhibit extrabinomial variation when the responses arise naturally in groups or "litters." This paper investigates the use of generalized Wald and score statistics for robustifying the standard inference methods based on the binomial likelihood. Special attention is given to the probit analysis of a parallel assay of the teratogenic effects on mice of several dioxins. Keywords: Empirical variance; Goodness of fit; Logistic regression; Probit analysis; Score tests; Teratology 1 Introduction Logistic regression and probit analysis are often used in dose-response modeling of binary responses where binomial likelihoods form the basis for a well-developed theory of estimation and inference (e.g., Cox and Snell, 1989, Hosmer and Lemeshow, 1989, and Santner and Duffy, 1989). In certain situations, however, the binary responses arise naturally in groups or "litters" and a binomial likelihood description of the data is not correct due to induced correlations w...