Causal Risk Ratio and Causal Risk Difference in Longitudinal Studies With Frequent Outcome Events

Causal Risk Ratio and Causal Risk Difference in Longitudinal Studies With Frequent Outcome Events

Marginal structural models (MSMs) are recognized as useful methods for addressing the issue of time-varying confounding in longitudinal studies. In the analyses of longitudinal data with binary outcomes, using the generalized estimating equation (GEE) logistic regression model within the MSM framewo...

Full description

Saved in:
Bibliographic Details
Main Authors: Hiroyuki Shiiba, Hisashi Noma, Keisuke Kuwahara, Tohru Nakagawa, Tetsuya Mizoue
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Data Science in Science
Subjects:
Longitudinal study
time-varying confounder
marginal structural model
risk ratio
risk difference
Online Access:https://www.tandfonline.com/doi/10.1080/26941899.2025.2527144
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items