artcat: Sample-size calculation for an ordered categorical outcome

• Autores: Ian R. White, Ella Marley Zagar, Tim P. Morris, Mahesh K. B. Parmar, Patrick Royston, Abdel G. Babiker
• Localización: The Stata journal, ISSN 1536-867X, Vol. 23, Nº. 1, 2023, págs. 3-23
• Idioma: inglés
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• Resumen

  • 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.