A leave-one-out cross-validation SAS macro for the identification of markers associated with survival
Christel Rushing1, Anuradha Bulusu1, Herbert I Hurwitz2
1Department of Biostatistics and Bioinformatics & Duke Cancer Biostatistics, Duke University School of Medicine, Durham, NC, United States.
Abstract:
A proper internal validation is necessary for the development of a reliable and reproducible prognostic model for external validation. Variable selection is an important step for building prognostic models. However, not many existing approaches couple the ability to specify the number of covariates in the model with a cross-validation algorithm. We describe a user-friendly SAS macro that implements a score selection method and a leave-one-out cross-validation approach. We discuss the method and applications behind this algorithm, as well as details of the SAS macro.
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