Document Detail

Conditional and exact tests in crossover trials.
MedLine Citation:
PMID:  10709805     Owner:  NLM     Status:  MEDLINE    
Generalized linear models are developed for crossover trials with no carryover effects and fixed subject effects. A general multinominal model for the distribution of data is considered. This subsumes both binary and categorical data. Conditional inferences eliminate subject effects by conditioning on their sufficient statistics. For normal data, least-squares analysis is exact with identical treatment inferences from unconditional and conditional analyses. For Poisson data, unconditional and conditional analyses are also identical, but for multinomial data this is not the case and the unconditional analysis is invalid. For multinomial data, asymptotic tests of both treatment effects and goodness of fit are unreliable with small samples. Procedures for exact tests are developed to overcome such problems, using enumeration, random sampling, and a hybrid of importance sampling and enumeration. A four-period binary crossover trial is used to illustrate an exact test of treatment effects by a two-stage sampling procedure based on a factorization of the conditional distribution of the sufficient statistics. An exact test of goodness of fit on the same data illustrates a two-stage scheme mixing importance sampling and enumeration.
M Patefield
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of biopharmaceutical statistics     Volume:  10     ISSN:  1054-3406     ISO Abbreviation:  J Biopharm Stat     Publication Date:  2000 Feb 
Date Detail:
Created Date:  2000-04-17     Completed Date:  2000-04-17     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  9200436     Medline TA:  J Biopharm Stat     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  109-29     Citation Subset:  IM    
Department of Applied Statistics, The University of Reading, United Kingdom.
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MeSH Terms
Binomial Distribution
Cross-Over Studies
Double-Blind Method
Likelihood Functions
Multivariate Analysis
Poisson Distribution
Randomized Controlled Trials as Topic / methods*
Sampling Studies
Statistics as Topic / methods*

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