Document Detail


Comparing Multiple Sensitivities and Specificities with Different Diagnostic Criteria: Applications to Sexual Abuse and Sexual Health Research.
MedLine Citation:
PMID:  19727430     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
When comparing sensitivities and specificities from multiple diagnostic tests, particularly in biomedical research, the different test kits under study are applied to groups of subjects with the same disease status for a disease or medical condition under consideration. Although this process gives rise to clustered or correlated test outcomes, the associated inference issues are well recognized and have been widely discussed in the literature. In mental health and psychosocial research, sensitivity and specificity have also been widely used to study the reliability of instrument for diagnosing mental health and psychiatric conditions and assessing certain behavioral patterns. However, unlike biomedical applications, outcomes are often obtained under varying reference standards or different diagnostic criteria, precluding the application of existing methods for comparing multiple diagnostic tests to such a research setting. In this paper, we develop a new approach to address these problems (including that of missing data) by extending recent work on inference using inverse probability weighted estimates. The approach is illustrated with data from two studies in sexual abuse and health research as well as a limited simulation study, with the latter used to study the performance of the proposed procedure.
Authors:
Q Yu; W Tang; Y Ma; S A Gamble; X M Tu
Publication Detail:
Type:  JOURNAL ARTICLE    
Journal Detail:
Title:  Computational statistics & data analysis     Volume:  53     ISSN:  -     ISO Abbreviation:  Comput Stat Data Anal     Publication Date:  2008 Sep 
Date Detail:
Created Date:  2009-9-3     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100960938     Medline TA:  Comput Stat Data Anal     Country:  -    
Other Details:
Languages:  ENG     Pagination:  27-37     Citation Subset:  -    
Affiliation:
Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY 14642.
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Descriptor/Qualifier:
Grant Support
ID/Acronym/Agency:
R01 DA018935-04//NIDA NIH HHS; R01 MH060285-04//NIMH NIH HHS; R24 MH071604-01A2//NIMH NIH HHS; UL1 RR024160-01//NCRR NIH HHS

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