title: The analysis of categorical data from cross-over trials using a latent variable model.
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.
authors.affiliation: Department of Applied Statistics, University of Reading, Whiteknights, U.K.
authors.forename: M G
authors.initials: MG
authors.lastname: Kenward
authors.forename: B
authors.initials: B
authors.lastname: Jones
mesh_terms: D000704:Analysis of Variance; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004412:Dysmenorrhea / Q000628:therapy; D005163:Factor Analysis, Statistical; D005260:Female; D006801:Humans; D016014:Linear Models; D008137:Longitudinal Studies; D008432:Mathematical Computing; D015233:Models, Statistical; D016017:Odds Ratio; D011336:Probability; D016032:Randomized Controlled Trials as Topic / Q000379:methods*