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Time-varying effect moderation using the structural nested mean model: estimation using inverse-weighted regression with residuals
This article considers the problem of examining time-varying causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and possible confounders are time varying. The structural nested mean model (SNMM) is used to specify the moderated time-varying caus...
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| 主要な著者: | , , , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2013
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4008726/ https://ncbi.nlm.nih.gov/pubmed/23873437 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sim.5892 |
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