Estimation of time-varying treatment effects using marginal structural models dependent on partial treatment history

[2412.08042] Estimation of time-varying treatment effects using marginal structural models dependent on partial treatment history Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Statistics > Methodology arXiv:2412.08042 (stat) [Submitted on 11 Dec 2024 ( v1 ), last revised 14 Jan 2026 (this version, v3)] Title: Estimation of time-varying treatment effects using marginal structural models dependent on partial treatment history Authors: Nodoka Seya , Masataka Taguri , Takeo Ishii View a PDF of the paper titled Estimation of time-varying treatment effects using marginal structural models dependent on partial treatment history, by Nodoka Seya and 1 other authors View PDF HTML (experimental) Abstract: Inverse probability (IP) weighting of marginal structural models (MSMs) can provide consistent estimators of time-varying treatment effects under correct model specifications and identifiability assumptions, even in the presence of time-varying confounding. However, this method has two problems: (i) inefficiency due to IP-weights cumulating all time points and (ii) bias and inefficiency due to the MSM misspecification. To address these problems, we propose (i) new IP-weights for estimating parameters of the MSM that depends on partial treatment history and (ii) closed testing procedures for selecting partial treatment history (how far back in time the MSM depends on past treatments). We derive the theoretical properties of our proposed methods under known IP-weights and discuss their extension to estimated IP-weights. Although some of our theoretical results are derived under additional assumptions beyond standard identifiability assumptions, some of which can be checked empirically from the data. In simulation studies, our proposed methods outperformed existing methods both in terms of performance in estimating time-varying treatment effects and in selecting partial treatment history. Our proposed methods have also been applied to real data of hemodialysis patients with reasonable results. Subjects: Methodology (stat.ME) Cite as: arXiv:2412.08042 [stat.ME] (or arXiv:2412.08042v3 [stat.ME] for this version) https://doi.org/10.48550/arXiv.2412.08042 Focus to learn more arXiv-issued DOI via DataCite Related DOI : https://doi.org/10.1515/jci-2025-0036 Focus to learn more DOI(s) linking to related resources Submission history From: Nodoka Seya [ view email ] [v1] Wed, 11 Dec 2024 02:45:48 UTC (610 KB) [v2] Thu, 29 May 2025 10:35:05 UTC (615 KB) [v3] Wed, 14 Jan 2026 05:45:26 UTC (830 KB) Full-text links: Access Paper: View a PDF of the paper titled Estimation of time-varying treatment effects using marginal structural models dependent on partial treatment history, by Nodoka Seya and 1 other authors View PDF HTML (experimental) TeX Source view license Current browse context: stat.ME < prev | next > new | recent | 2024-12 Change to browse by: stat References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... 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