Simultaneous confidence intervals using ordinal effect measures for ordered categorical outcomes

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

When outcomes are ordered categorical, a model using an ordinal effect size measure is a good alternative of the cumulative logit model to compare several independent group differences. We present a method of constructing simultaneous confidence intervals for the ordinal effect size measures, using the studentized range distribution with the score test statistic. A simulation study shows that the proposed method performs well in terms of coverage probability, and it seems better than the method using a Bonferroni correction for Wald-type statistics and methods that account for the dependencies among pairwise ordinal effect size measures using the multivariate normal distribution (or the multivariate t-distribution for small samples).

Original languageEnglish (US)
Pages (from-to)3179-3188
Number of pages10
JournalStatistics in Medicine
Volume28
Issue number25
DOIs
StatePublished - Nov 10 2009

Keywords

  • Bonferroni correction
  • Ordinal effect size measure
  • Score test
  • Simultaneous confidence interval
  • Studentized range distribution

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

Fingerprint Dive into the research topics of 'Simultaneous confidence intervals using ordinal effect measures for ordered categorical outcomes'. Together they form a unique fingerprint.

Cite this