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...

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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
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Online Access:https://www.tandfonline.com/doi/10.1080/26941899.2025.2527144
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