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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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Data Science in Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/26941899.2025.2527144 |
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