ID | 69029 |
著者 |
Suzuki, Etsuji
Department of Epidemiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
Kaken ID
publons
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抄録 | Methods for causal mediation analysis have developed dramatically over the past few decades.1–7 In the causal mediation literature, several causal quantities—or estimands—have been proposed, including natural direct and indirect effects, interventional direct and indirect effects, and separable direct and indirect effects. As another possible causal estimand, Chen and Lin8 proposed separable path-specific effects, which is an extension of the separable effects framework to cases that involve multiple ordered mediators. In this commentary, I briefly discuss the newly proposed method from a broader perspective on causal mediation analysis. For readers less familiar with common causal mediation approaches, please see related literature.1–3,9–11
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備考 | This is a non-final version of an article published in final form in Suzuki, Etsujia. L or M1—Critical Challenges in Mediation Analysis. Epidemiology 36(5):p 686-689, September 2025. | DOI: 10.1097/EDE.0000000000001888.
This fulltext file will be available in Sep. 2026.
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発行日 | 2025-09
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出版物タイトル |
Epidemiology
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巻 | 36巻
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号 | 5号
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出版者 | Ovid Technologies (Wolters Kluwer Health)
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開始ページ | 686
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終了ページ | 689
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ISSN | 1044-3983
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NCID | AA10832184
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資料タイプ |
学術雑誌論文
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言語 |
英語
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OAI-PMH Set |
岡山大学
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著作権者 | © 2025 Wolters Kluwer Health, Inc.
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論文のバージョン | author
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PubMed ID | |
DOI | |
関連URL | isVersionOf https://doi.org/10.1097/ede.0000000000001888
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Citation | Suzuki, Etsujia. L or M1—Critical Challenges in Mediation Analysis. Epidemiology 36(5):p 686-689, September 2025. | DOI: 10.1097/EDE.0000000000001888
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助成情報 |
23K09740:
因果関係の可視化:メカニズムの観点から描くグラフィカルモデルの開発と実用
( 独立行政法人日本学術振興会 / Japan Society for the Promotion of Science )
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