title: Resampling and cross-validation techniques: a tool to reduce bias caused by model building?
abstract: The process of model building involved in the analysis of many medical studies may lead to a considerable amount of over-optimism with respect to the predictive ability of the 'final' regression model. In this paper we illustrate this phenomenon in a simple cutpoint model and explore to what extent bias can be reduced by using cross-validation and bootstrap resampling. These computer intensive methods are compared to an ad hoc approach and to a heuristic method. Besides illustrating all proposals with the data from a breast cancer study we perform a simulation study in order to assess the quality of the methods.
authors.affiliation: Institute of Medical Biometry and Informatics, University of Freiburg, Germany.
authors.forename: M
authors.initials: M
authors.lastname: Schumacher
authors.forename: N
authors.initials: N
authors.lastname: Holländer
authors.forename: W
authors.initials: W
authors.lastname: Sauerbrei
mesh_terms: D015982:Bias; D001943:Breast Neoplasms / Q000175:diagnosis; D003198:Computer Simulation; D004273:DNA, Neoplasm / Q000032:analysis; D018572:Disease-Free Survival; D005260:Female; D005434:Flow Cytometry; D006801:Humans; D015233:Models, Statistical; D011379:Prognosis; D012044:Regression Analysis; D015203:Reproducibility of Results; D012107:Research Design
chemical_list: D004273:DNA, Neoplasm