Model Checking for Logistic Regression: A Conditional Approach,

Abstract

We review the use of exact methods for checking logistic regression models. We focus on global model checks, outlier detection, and goodness-of-link checks. We discuss approximations to exact conditional methods whenever available. We also contrast exact conditional methods and standard unconditional methods based on asymptotic approximations. The techniques are applied to two examples.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1992
Accession Number
ADP007136

Entities

People

  • Edward J. Bedrick
  • Joe R. Hill

Organizations

  • University of New Mexico

Tags

DTIC Thesaurus Topics

  • Anomaly Detection
  • Change Detection
  • Computer Science
  • Contrast
  • Data Science
  • Detection
  • Engineering
  • Information Science
  • Network Science
  • Standards
  • Statistics
  • Theoretical Computer Science

Fields of Study

  • Mathematics

Readers

  • Statistical inference.