首页   按字顺浏览 期刊浏览 卷期浏览 Analyzing an ordinal pharmaceutical data set with a categorical covariate using monoton...
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.

 

点击下载:  PDF (457KB)



返 回