Testing goodness-of-fit of a logistic regression model with case-control data

K. F. Cheng, L. C. Chen

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

A new test is proposed for testing the validity of the logistic regression model based on case-control data. The proposed test does not need a partition of the space of explanatory variables to handle the case of nonreplication. The new test is consistent against very general alternatives. The asymptotic distribution of the test statistic under a sequence of local alternatives is derived so that the behavior of the asymptotic power function of the new test can be studied. This result also gives the approximated null distribution of the test statistic. For practical sample sizes, the adequacy of the large-sample approximation to the null distribution of the test statistic are carefully examined. Power comparisons with other goodness-of-fit tests are performed to show the advantages of the new method. The test statistic is very simple to compute and the new test will be illustrated with examples.

Original languageEnglish
Pages (from-to)409-422
Number of pages14
JournalJournal of Statistical Planning and Inference
Volume124
Issue number2
DOIs
Publication statusPublished - Sep 1 2004
Externally publishedYes

Keywords

  • Asymptotic distribution
  • Asymptotic power
  • Case-control data
  • Goodness of fit
  • Logistic regression

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Statistics and Probability

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