TITLE

Combining longitudinal discriminant analysis and partial area under the ROC curve to predict non-response to treatment for hepatitis C virus

AUTHOR(S)
Lukasiewicz, Esther; Gorfine, Malka; Neumann, Avidan U; Freedman, Laurence S
PUB. DATE
June 2011
SOURCE
Statistical Methods in Medical Research;Jun2011, Vol. 20 Issue 3, p275
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
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.
ACCESSION #
60979556

 

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