Bootstrap internal validation command for predictive logistic regression models

B. M. Fernandez-Felix (), E. García-Esquinas, A. Muriel, A. Royuela and J. Zamora
Additional contact information
B. M. Fernandez-Felix: Clinical Biostatistics Unit Hospital Ramón y Cajal (IRYCIS)
E. García-Esquinas: Autonomous University of Madrid
A. Muriel: Clinical Biostatistics Unit Hospital Ramón y Cajal (IRYCIS)
A. Royuela: Puerta de Hierro Biomedical Research Institute
J. Zamora: Clinical Biostatistics Unit Hospital Ramón y Cajal (IRYCIS)

Stata Journal, 2021, vol. 21, issue 2, 498-509

Abstract: Overfitting is a common problem in the development of predictive models. It leads to an optimistic estimation of apparent model performance. Internal validation using bootstrapping techniques allows one to quantify the optimism of a predictive model and provide a more realistic estimate of its performance mea- sures. Our objective is to build an easy-to-use command, bsvalidation, aimed to perform a bootstrap internal validation of a logistic regression model.

Keywords: bsvalidation; bootstrap; internal validation; predictive model; performance; logistic; logit (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1177/1536867X211025836

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