The Confidence Intervals for Logistic Model in Contingency Table

Cho, Tae-Kyoung

  • Published : 2003.12.01


We can use the logistic model for categorical data when the response variables are binary data. In this paper we consider the problem of constructing the confidence intervals for logistic model in I${\times}$J${\times}$2 contingency table. These constructions are simplified by applying logit transformation. This transforms the problem to consider linear form which called the logit model. After obtaining the confidence intervals for the logit model, the reverse transform is applied to obtain the confidence intervals for the logistic model.


logistic model;contingency table;logit model


  1. Analysis of Qualitative Data v.1 Haberman,S.J.
  2. measures of Association for Cross classifications Goodman,L.A.;Kruskal,W.H.
  3. The Analysis of Binary Data Cox,D.R.
  4. J. Roy. Statist. Soc. B v.43 On the existence of maximum likelihood estimators for the binomial response models Silvapull,M.J.
  5. Biometrika v.71 On the Existence Maximum Likelihood Estimates in Logistic Models Albert,A.;Anderson,J.A.
  6. Biometrics v.14 Fitting the Logistic by Maximum Likelihood Hodges,J.L.,Jr.
  7. Nonlinear Parameter Estimates Bard,Y.
  8. SAS/IML SAS Institute Inc.