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artcat: Sample-size calculation for an ordered categorical outcome

White, Ian R; Marley-Zagar, Ella; Morris, Tim P; Parmar, Mahesh KB; Royston, Patrick; Babiker, Abdel G; (2023) artcat: Sample-size calculation for an ordered categorical outcome. The Stata Journal , 23 (1) pp. 3-23. 10.1177/1536867x231161934. Green open access

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Abstract

We describe a new command, artcat, that calculates sample size or power for a randomized controlled trial or similar experiment with an ordered categorical outcome, where analysis is by the proportional-odds model. artcat implements the method of Whitehead (1993, Statistics in Medicine 12: 2257–2271). We also propose and implement a new method that 1) allows the user to specify a treatment effect that does not obey the proportional-odds assumption, 2) offers greater accuracy for large treatment effects, and 3) allows for noninferiority trials. We illustrate the command and explore the value of an ordered categorical outcome over a binary outcome in various settings. We show by simulation that the methods perform well and that the new method is more accurate than Whitehead’s method.

Type: Article
Title: artcat: Sample-size calculation for an ordered categorical outcome
Open access status: An open access version is available from UCL Discovery
DOI: 10.1177/1536867x231161934
Publisher version: https://doi.org/10.1177/1536867X231161934
Language: English
Additional information: © StataCorp LLC 2023. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/).
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10168833
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