对 Chen 和 Heitjan 的 "不完全依从性临床试验中估计值的敏感性 "的评论

IF 1 4区数学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY

International Journal of Biostatistics Pub Date : 2024-07-27 DOI:10.1515/ijb-2023-0127

Stuart G. Baker, Karen S. Lindeman

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引用次数: 0

摘要

Chen and Heitjan (Sensitivity of estimands in clinical trials with imperfect compliance.Int J Biostat.2023）使用线性外推法，在全遵从或无遵从的多项随机试验中，从遵从者平均因果效应（CACE）估算出人群平均因果效应（PACE）。在这种情况下，以及在涉及前后研究中不同治疗可用性的配对可用性设计中，要从 CACE 外推到 PACE，我们推荐使用 Baker 和 Lindeman（《因果推论》，2013 年）中的敏感性分析，因为它不局限于线性模型，还涉及各种随机效应和趋势模型。

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

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.

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来源期刊

International Journal of Biostatistics MATHEMATICAL & COMPUTATIONAL BIOLOGY-STATISTICS & PROBABILITY

CiteScore

2.10

自引率

8.30%

发文量

审稿时长

>12 weeks

期刊介绍： The International Journal of Biostatistics (IJB) seeks to publish new biostatistical models and methods, new statistical theory, as well as original applications of statistical methods, for important practical problems arising from the biological, medical, public health, and agricultural sciences with an emphasis on semiparametric methods. Given many alternatives to publish exist within biostatistics, IJB offers a place to publish for research in biostatistics focusing on modern methods, often based on machine-learning and other data-adaptive methodologies, as well as providing a unique reading experience that compels the author to be explicit about the statistical inference problem addressed by the paper. IJB is intended that the journal cover the entire range of biostatistics, from theoretical advances to relevant and sensible translations of a practical problem into a statistical framework. Electronic publication also allows for data and software code to be appended, and opens the door for reproducible research allowing readers to easily replicate analyses described in a paper. Both original research and review articles will be warmly received, as will articles applying sound statistical methods to practical problems.