Document Detail


Treatment-patient interactions for diagnostics of cross-over trials.
MedLine Citation:
PMID:  9304766     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In cross-over trials, various types of responses may be recorded, not all of which can be appropriately modelled by a Normal distribution. Widening the class of models to the generalized linear model family has a number of advantages. An important one is that certain interactions, especially that between patients and treatments, can easily be fitted for frequency and count data. These can be used as diagnostics for the fit of the model used. One handicap has been the frequentist difficulty of comparing the fit of different non-nested models in this family. This can be overcome by the use of a model selection criterion such as the Akaike or Bayesian information criterion. This approach to modelling and diagnostics for cross-over trials is applied to two studies involving small counts of anginal attacks, previously analysed in the literature using classical Normal techniques.
Authors:
J K Lindsey; B Jones
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Statistics in medicine     Volume:  16     ISSN:  0277-6715     ISO Abbreviation:  Stat Med     Publication Date:  1997 Sep 
Date Detail:
Created Date:  1997-11-20     Completed Date:  1997-11-20     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  8215016     Medline TA:  Stat Med     Country:  ENGLAND    
Other Details:
Languages:  eng     Pagination:  1955-64     Citation Subset:  IM    
Affiliation:
Department of Medical Statistics, School of Computing Sciences, De Montfort University, Leicester, U.K.
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MeSH Terms
Descriptor/Qualifier:
Clinical Trials as Topic / statistics & numerical data*
Cross-Over Studies*
Humans
Likelihood Functions
Linear Models*
Normal Distribution
Poisson Distribution
Research Design

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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