Comments on “sensitivity of estimands in clinical trials with imperfect compliance” by Chen and Heitjan

Baker Stuart G. () and Lindeman Karen S.
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Baker Stuart G.: National Cancer Institute, Bethesda, MD, 20892-9789, USA
Lindeman Karen S.: Department of Anesthesiology, Johns Hopkins Medical Institutions, Baltimore, USA

The International Journal of Biostatistics, 2024, vol. 20, issue 2, 435-436

Abstract: Chen and Heitjan (Sensitivity of estimands in clinical trials with imperfect compliance. Int J Biostat. 2023) used linear extrapolation to estimate the population average causal effect (PACE) from the complier average causal effect (CACE) in multiple randomized trials with all-or-none compliance. For extrapolating from CACE to PACE in this setting and in the paired availability design involving different availabilities of treatment among before-and-after studies, we recommend the sensitivity analysis in Baker and Lindeman (J Causal Inference, 2013) because it is not restricted to a linear model, as it involves various random effect and trend models.

Keywords: complier average causal effect; local average treatment effect; paired availability design; noncompliance; principal stratification randomized trial (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1515/ijb-2023-0127

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