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Simultaneous confidence intervals using ordinal effect measures for ordered categorical outcomes
1Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, U.S.A. ryu.euijung@mayo.edu
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).
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