Noncollapsibility and its role in quantifying confounding bias in logistic regression

Noncollapsibility and its role in quantifying confounding bias in logistic regression

Abstract Background Confounding bias is a common concern in epidemiological research. Its presence is often determined by comparing exposure effects between univariable- and multivariable regression models, using an arbitrary threshold of a 10% difference to indicate confounding bias. However, many...

Full description

Bibliographic Details
Main Authors: Noah A. Schuster, Jos W. R. Twisk, Gerben ter Riet, Martijn W. Heymans, Judith J. M. Rijnhart
Format: Article
Language:English
Published: BMC 2021-07-01
Series:BMC Medical Research Methodology
Subjects:
Logistic regression
Confounding
Noncollapsibility
Confounder-adjustment
Univariable regression analysis
Multivariable regression analysis
Online Access:https://doi.org/10.1186/s12874-021-01316-8

Internet

https://doi.org/10.1186/s12874-021-01316-8

Similar Items