Improved transformed deviance statistic for testing a logistic regression model

• Taneichi, Nobuhiro

• Sekiya, Yuri

• Toyama, Jun

Abstract

In logistic regression models, we consider the deviance statistic (the log likelihood ratio statistic) D as a goodness-of-fit test statistic. In this paper, we show the derivation of an expression of asymptotic expansion for the distribution of D under a null hypothesis. Using the continuous term of the expression, we obtain a Bartlett-type transformed statistic D˜ that improves the speed of convergence to the chi-square limiting distribution of D. By numerical comparison, we find that the transformed statistic D˜ performs much better than D. We also give a real data example of D˜ being more reliable than D for testing a hypothesis.

Journal

• Journal of Multivariate Analysis

  Journal of Multivariate Analysis 102 (9), 1263-1279, 2011-10

  Elsevier

Keywords

• Bartlett adjustment
• Deviance
• Edgeworth expansion
• Logistic regression

Details

• CRID: 1050564288961825280
• NII Article ID: 120003444297
• DOI: 10.1016/j.jmva.2011.04.010
• HANDLE: 2115/47351
• ISSN: 0047259X
• Web Site: https://api.elsevier.com/content/article/PII:S0047259X11000662?httpAccept=text/xml
• Web Site: https://api.elsevier.com/content/article/PII:S0047259X11000662?httpAccept=text/plain
• Text Lang: en
• Article Type: journal article
• Data Source:
  • IRDB
  • Crossref
  • CiNii Articles
  • KAKEN