Bootstrap internal validation command for predictive logistic regression models

B. M. Fernandez-Felix; E. García-Esquinas; A. Muriel; A. Royuela; J. Zamora

doi:10.1177/1536867X211025836

Bootstrap internal validation command for predictive logistic regression models

B. M. Fernandez-Felix
, E. García-Esquinas
, A. Muriel
, A. Royuela
, J. Zamora

Metabolism and Systems Science

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

571 Downloads (Pure)

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 measures. Our objective is to build an easy-to-use command, bsvalidation, aimed to perform a bootstrap internal validation of a logistic regression model.

Original language	English
Pages (from-to)	498-509
Number of pages	12
Journal	Stata Journal
Volume	21
Issue number	2
DOIs	https://doi.org/10.1177/1536867X211025836
Publication status	Published - 29 Jun 2021

Bibliographical note

Publisher Copyright:
© StataCorp LLC 2021.

Keywords

bootstrap
bsvalidation
internal validation
logistic
logit
performance
predictive model
st0644

ASJC Scopus subject areas

Mathematics (miscellaneous)

Access to Document

10.1177/1536867X211025836Licence: None: All rights reserved

Fernandez-FelixB2021Bootstrap_submitted
Final published version: Fernandez-Felix, B. M., García-Esquinas, E., Muriel, A., Royuela, A., & Zamora, J. (2021). Bootstrap internal validation command for predictive logistic regression models. The Stata Journal, 21(2), 498-509. © StataCorp LLC 2021. https://doi.org/10.1177/1536867X211025836
Submitted manuscript, 400 KBLicence: Creative Commons: Attribution-NoDerivs (CC BY-ND)

Cite this

@article{06587d1530e14cfbb8bfc91185602daa,

title = "Bootstrap internal validation command for predictive logistic regression models",

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 measures. Our objective is to build an easy-to-use command, bsvalidation, aimed to perform a bootstrap internal validation of a logistic regression model.",

keywords = "bootstrap, bsvalidation, internal validation, logistic, logit, performance, predictive model, st0644",

author = "Fernandez-Felix, \{B. M.\} and E. Garc{\'i}a-Esquinas and A. Muriel and A. Royuela and J. Zamora",

note = "Publisher Copyright: {\textcopyright} StataCorp LLC 2021.",

year = "2021",

month = jun,

day = "29",

doi = "10.1177/1536867X211025836",

language = "English",

volume = "21",

pages = "498--509",

journal = "Stata Journal",

issn = "1536-867X",

publisher = "StataCorp",

number = "2",

}

TY - JOUR

T1 - Bootstrap internal validation command for predictive logistic regression models

AU - Fernandez-Felix, B. M.

AU - García-Esquinas, E.

AU - Muriel, A.

AU - Royuela, A.

AU - Zamora, J.

N1 - Publisher Copyright: © StataCorp LLC 2021.

PY - 2021/6/29

Y1 - 2021/6/29

N2 - 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 measures. Our objective is to build an easy-to-use command, bsvalidation, aimed to perform a bootstrap internal validation of a logistic regression model.

AB - 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 measures. Our objective is to build an easy-to-use command, bsvalidation, aimed to perform a bootstrap internal validation of a logistic regression model.

KW - bootstrap

KW - bsvalidation

KW - internal validation

KW - logistic

KW - logit

KW - performance

KW - predictive model

KW - st0644

UR - https://www.scopus.com/pages/publications/85109030040

U2 - 10.1177/1536867X211025836

DO - 10.1177/1536867X211025836

M3 - Article

AN - SCOPUS:85109030040

SN - 1536-867X

VL - 21

SP - 498

EP - 509

JO - Stata Journal

JF - Stata Journal

IS - 2

ER -

Bootstrap internal validation command for predictive logistic regression models

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this