Document Detail


Combining longitudinal discriminant analysis and partial area under the ROC curve to predict non-response to treatment for hepatitis C virus.
MedLine Citation:
PMID:  20200199     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
A longitudinal discriminant analysis is applied to build predictive models based on repeated measurements of serum hepatitis C virus RNA. These models are evaluated through the partial area under the receiver operating curve index (PA index) and, the final selection of the best model is based on cross-validated estimates of the PA index. Models are compared by building 95% bootstrap confidence interval for the difference in PA index between two models. Data from a randomised trial, in which chronic HCV patients were enrolled, are used to illustrate the application of the proposed method to predict treatment outcome.
Authors:
Esther Lukasiewicz; Malka Gorfine; Avidan U Neumann; Laurence S Freedman
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Publication Detail:
Type:  Journal Article     Date:  2010-03-03
Journal Detail:
Title:  Statistical methods in medical research     Volume:  20     ISSN:  1477-0334     ISO Abbreviation:  Stat Methods Med Res     Publication Date:  2011 Jun 
Date Detail:
Created Date:  2011-05-25     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9212457     Medline TA:  Stat Methods Med Res     Country:  England    
Other Details:
Languages:  eng     Pagination:  275-89     Citation Subset:  IM    
Affiliation:
Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel and Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, Israel. estherh@gertner.health.gov.il.
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