SEMIPARAMETRIC AND NONPARAMETRIC METHODS FOR THE ANALYSIS OF REPEATED MEASUREMENTS WITH APPLICATIONS TO CLINICAL-TRIALS

被引：66

作者：

DAVIS, CS

机构：

[1] Department of Preventive Medicine, University of Iowa, Iowa, Iowa, 52242

来源：

STATISTICS IN MEDICINE | 1991年 / 10卷 / 12期

关键词：

D O I：

10.1002/sim.4780101210

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Techniques applicable for the analysis of longitudinal data when the response variable is non-normal are not nearly as comprehensive as for normally-distributed outcomes. However, there have been several recent developments. Semi-parametric and non-parametric methodology for the analysis of repeated measurements is reviewed. The commonly encountered design in which, for each subject, one assesses a univariate response variable at multiple fixed time points, is considered. The types of outcomes considered include binary, ordered categorical, and continuous (but extremely non-normal) response variables. All of the methods considered allow for incomplete data due to the occurrence of missing observations. In addition, discrete and/or continuous covariates, which may be time-dependent, are accommodated by some of the approaches. The methods are demonstrated using data from three clinical trials.

引用

页码：1959 / 1980

页数：22

共 42 条

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