The scientific foundation of a modern clinical trial is randomization – each patient is randomized to a treatment group, and statistical comparisons are made between treatment groups. Because the study units are individual patients, this ‘one patient, one vote’ principle needs to be followed – both in study design and in data analysis. From the physicians' point of view, each patient is equally important, and they need to be treated equally in data analysis. It is critical that statistical analysis should respect design and study design is based on randomization. Hence from both statistical and medical points of view, data analysis needs to follow this ‘one patient, one vote’ principle. Under ICH E9 (R1), five strategies are recommended to establish ‘estimand’. This paper discusses how to implement these strategies using the ‘one patient, one vote’ principle.

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To cite this article: Naitee Ting (2023) How to implement the ‘one patient, one vote’ principle under the framework of estimand, Statistical Theory and Related Fields, 7:3, 202-212, DOI: 10.1080/24754269.2023.2164943

To link to this article: https://doi.org/10.1080/24754269.2023.2164943