OUTLIER TESTS FOR LOGISTIC-REGRESSION - A CONDITIONAL APPROACH
成果类型：
Article
署名作者：
BEDRICK, EJ; HILL, JR
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/77.4.815
发表日期：
1990
页码：
815827
关键词：
摘要：
We consider exact conditional methods for identifying outliers in logistic regression data. Tests for a single outlier and multiple outliers are developed assuming a logistic slippage model. The p-values for these tests are determined using an explicit enumeration of all possible responses consistent with the observed value of the sufficient statistic. Justifications are given for preferring this computationally intensive approach to standard methods based on asymptotic approximations. The techniques are applied to two examples.