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.
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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-pp.ucl.ac.uk/id/eprint/10168833 |
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