Document Detail


Applying concepts of generalizability theory on clinical trial data to investigate sources of variation and their impact on reliability.
MedLine Citation:
PMID:  15737106     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
This work aims at applying concepts of generalizability theory to data resulting from clinical trials. The focus is to study the sources of variance and their impact on the reliability and generalizability of a psychiatric measurement scale. The goal is to identify, measure, and thereby potentially find strategies to reduce the influence of these sources on the measurement in question for future trials. This approach was originally devised by Cronbach and his associates and is known as generalizability theory. This work shows how full modeling power in mixed models can be used to study generalizability using data from five double-blind randomized clinical trials, comparing the effects of risperidone to conventional antipsychotic agents for the treatment of chronic schizophrenia.
Authors:
Tony Vangeneugden; Annouschka Laenen; Helena Geys; Didier Renard; Geert Molenberghs
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Biometrics     Volume:  61     ISSN:  0006-341X     ISO Abbreviation:  Biometrics     Publication Date:  2005 Mar 
Date Detail:
Created Date:  2005-03-01     Completed Date:  2005-06-30     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  0370625     Medline TA:  Biometrics     Country:  United States    
Other Details:
Languages:  eng     Pagination:  295-304     Citation Subset:  IM    
Affiliation:
Johnson & Johnson Pharmaceutical Research & Development, B-2340 Beerse, Belgium. tvangene@tibbe.jnj.com
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MeSH Terms
Descriptor/Qualifier:
Antipsychotic Agents / therapeutic use
Biometry
Clinical Trials as Topic / methods*
Humans
Models, Statistical*
Reproducibility of Results
Schizophrenia / drug therapy
Chemical
Reg. No./Substance:
0/Antipsychotic Agents

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


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