Binary Regression Models for Contaminated Data
讨论了二元回归数据中异常值的性质，提出一个允许少量二元响应被误记录的简单模型，并开发了相应的稳健估计和诊断技术。
SUMMARY The nature of outliers in the context of binary regression data is discussed. Resistant fitting procedures produce estimated regression coefficients which are numerically larger than maximum likelihood, implying the need for a shrinkage-type correction. A simple model which allows for a small number of the binary responses being misrecorded is proposed, and associated techniques for robust estimation and diagnostics developed.