Literature DB >> 1947516

The analysis of categorical data from cross-over trials using a latent variable model.

M G Kenward1, B Jones.   

Abstract

A latent variable model for categorical data is described. The nuisance parameters in the model can be eliminated from the analysis through the use of a conditional likelihood and this leads to an analysis based on a log-linear model. It is shown how the structure of a cross-over trial allows considerable simplification in the formulation of this model and routine application of well-known statistical packages. The method is illustrated by data from a three-period cross-over trial on the relief of primary dysmenorrhea using the GLIM and SAS packages.

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Year:  1991        PMID: 1947516     DOI: 10.1002/sim.4780101012

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  2 in total

1.  A note on misspecification in general linear models with correlated errors for the analysis of crossover clinical trials.

Authors:  Wei Wang; Ning Cong; Tian Chen; Hui Zhang; Bo Zhang
Journal:  PLoS One       Date:  2019-03-14       Impact factor: 3.240

2.  Design, Analysis, and Reporting of Crossover Trials for Inclusion in a Meta-Analysis.

Authors:  Tianjing Li; Tsung Yu; Barbara S Hawkins; Kay Dickersin
Journal:  PLoS One       Date:  2015-08-18       Impact factor: 3.240

  2 in total

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