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Repeated measures for two within-subject factors: analysis and missing data solutions.

作者信息

Schoemaker R C, van Houwelingen H C

机构信息

Centre for Human Drug Research, Leiden, The Netherlands.

出版信息

J Biopharm Stat. 1994 Jul;4(2):173-88. doi: 10.1080/10543409408835081.

DOI:10.1080/10543409408835081
PMID:7951273
Abstract

The statistical analysis of the repeated measures design with two factors within and no factors between subjects, which is popular in clinical pharmacology, is discussed. Use of restricted maximum likelihood (REML) methodology is compared to an imputation procedure in small sample situations with missing data and is illustrated by simulations. While imputation leads to undesirable results that are not easily corrected, REML estimation in which test statistics are compared to an F-distribution provides an elegant tool for the analysis of these designs.

摘要

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