Understanding Marginal Structural Models for Time-Varying Exposures: Pitfalls and Tips
Epidemiologists are increasingly encountering complex longitudinal data, in which exposures and their confounders vary during follow-up. When a prior exposure affects the confounders of the subsequent exposures, estimating the effects of the time-varying exposures requires special statistical techni...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Japan Epidemiological Association
2020-09-01
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Series: | Journal of Epidemiology |
Subjects: | |
Online Access: | https://www.jstage.jst.go.jp/article/jea/30/9/30_JE20200226/_pdf |