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artcat: Sample-size calculation for an ordered categorical outcome.
White, Ian R; Marley-Zagar, Ella; Morris, Tim P; Parmar, Mahesh K B; Royston, Patrick; Babiker, Abdel G.
Affiliation
  • White IR; MRC Clinical Trials Unit, University College London, London, U.K.
  • Marley-Zagar E; MRC Clinical Trials Unit, University College London, London, U.K.
  • Morris TP; MRC Clinical Trials Unit, University College London, London, U.K.
  • Parmar MKB; MRC Clinical Trials Unit, University College London, London, U.K.
  • Royston P; MRC Clinical Trials Unit, University College London, London, U.K.
  • Babiker AG; MRC Clinical Trials Unit, University College London, London, U.K.
Stata J ; 23(1): 3-23, 2023 Mar.
Article in En | MEDLINE | ID: mdl-37155554
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Clinical_trials / Prognostic_studies Language: En Journal: Stata J Year: 2023 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Clinical_trials / Prognostic_studies Language: En Journal: Stata J Year: 2023 Type: Article