Outlier tests for logistic regression: A conditional approach

Edward J. Bedrick, Joe R. Hill

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)815-827
Number of pages13
Issue number4
StatePublished - Dec 1990
Externally publishedYes


  • Exact inference
  • P-value
  • Residual

ASJC Scopus subject areas

  • Statistics and Probability
  • General Mathematics
  • Agricultural and Biological Sciences (miscellaneous)
  • General Agricultural and Biological Sciences
  • Statistics, Probability and Uncertainty
  • Applied Mathematics


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