Marginal and conditional confounding using logits

Karlson, K. B., Popham, F. and Holm, A. (2023) Marginal and conditional confounding using logits. Sociological Methods and Research, 52(4), pp. 1765-1784. (doi: 10.1177/0049124121995548) (PMID:37873547) (PMCID:PMC7615235)

Abstract

This article presents two ways of quantifying confounding using logistic response models for binary outcomes. Drawing on the distinction between marginal and conditional odds ratios in statistics, we define two corresponding measures of confounding (marginal and conditional) that can be recovered from a simple standardization approach. We investigate when marginal and conditional confounding may differ, outline why the method by Karlson, Holm, and Breen recovers conditional confounding under a “no interaction”-assumption, and suggest that researchers may measure marginal confounding by using inverse probability weighting. We provide two empirical examples that illustrate our standardization approach.

• Item Type: Articles
• Additional Information: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Frank Popham is funded by the Medical Research Council, UK (MC_UU_12017/13), and Chief Scientist Office, Scotland (SPHSU13).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Popham, Dr Frank
• Authors: Karlson, K. B., Popham, F., and Holm, A.
• College/School: College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > MRC/CSO SPHSU
• Journal Name: Sociological Methods and Research
• Publisher: SAGE Publications
• ISSN: 0049-1241
• ISSN (Online): 1552-8294
• Published Online: 09 April 2021
• Copyright Holders: Copyright © 2021 The Authors
• First Published: First published in Sociological Methods and Research 52(4):1765-1784
• Publisher Policy: Reproduced under a Creative Commons License

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
72765	1	Measuring and Analysing Socioeconomic Inequalities in Health	Alastair Leyland	Medical Research Council (MRC)	MC_UU_12017/13	HW - MRC/CSO Social and Public Health Sciences Unit
72765	1	Measuring and Analysing Socioeconomic Inequalities in Health	Alastair Leyland	Office of the Chief Scientific Adviser (CSO)	SPHSU13	HW - MRC/CSO Social and Public Health Sciences Unit