Siu Hung Cheung

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Koon Shing Kwong1
Yueqiong Lin1
1Koon Shing Kwong
1Yueqiong Lin
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In clinical studies, the proportional odds model is widely used to compare treatment efficacies when the responses are categorically ordered. However, this model has been shown to be inappropriate when the proportional odds assumption is invalid, mainly because it is unable to control the type I error rate in such circumstances. To remedy this problem, the(More)
Ordered categorical data are frequently encountered in clinical studies. A popular method for comparing the efficacy of treatments is to use logistic regression with the proportional odds assumption. The test statistic is based on the Wilcoxon-Mann-Whitney test. However, the proportional odds assumption may not be appropriate. In such cases, the probability(More)
Clinical trials frequently involve pairwise comparisons of different treatments to evaluate their relative efficacy. In this study, we examine methods for conducting pairwise tests of treatments with ordered categorical responses. A modified version of the Wilcoxon-Mann-Whitney test based on a logistic regression model assuming proportional odds is a(More)
In clinical studies, it is common to compare several treatments with a control. In such cases, the most popular statistical technique is the Dunnett procedure. However, the Dunnett procedure is designed to deal with particular families of inferences in which all hypotheses are either one sided or two sided. Recently, based on the minimization of average(More)
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