Analyzing an ordinal pharmaceutical data set with a categorical covariate using monotone-scores models
作者:
Christy Chuang,
期刊:
Communications in Statistics - Simulation and Computation
(Taylor Available online 1987)
卷期:
Volume 16,
issue 1
页码: 1-15
ISSN:0361-0918
年代: 1987
DOI:10.1080/03610918708812574
出版商: Marcel Dekker, Inc.
关键词: drug performance parameter;maximum likelihood estimation;monotone-scores model;ordinal data;response score;stochastic ordering;subgroup performance parameter
数据来源: Taylor
摘要:
Chuang and Agresti (1986) propose a monotone-scores model to analyze an ordinal pain data set from a pharmaceutical study where 4 analgesics were compared for their pain-relieving capabilities. In this paper, we generalize the model of Chuang and Agresti to incorporate an additional pre-test categorical variable. This generalization allows an ordering of the drugs conditional on a subject's pre-test categorical presentation. It also allows the identification of subjects who can most benefit from different drugs under comparison. These extensions are applied to part of a CNS study where an active drug was compared to a placebo and a pre-medication response to a placebo was available.
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