artcat: Sample-size calculation for an ordered categorical outcome
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, 12: 2257-2271). We also propose and...
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| Vydané v: | The Stata journal Ročník 23; číslo 1; s. 3 |
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| Hlavní autori: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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United States
01.03.2023
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| ISSN: | 1536-867X |
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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,
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. |
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| AbstractList | 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,
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. 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.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. |
| Author | Babiker, Abdel G Morris, Tim P White, Ian R Parmar, Mahesh K B Royston, Patrick Marley-Zagar, Ella |
| Author_xml | – sequence: 1 givenname: Ian R surname: White fullname: White, Ian R organization: MRC Clinical Trials Unit, University College London, London, U.K – sequence: 2 givenname: Ella surname: Marley-Zagar fullname: Marley-Zagar, Ella organization: MRC Clinical Trials Unit, University College London, London, U.K – sequence: 3 givenname: Tim P surname: Morris fullname: Morris, Tim P organization: MRC Clinical Trials Unit, University College London, London, U.K – sequence: 4 givenname: Mahesh K B surname: Parmar fullname: Parmar, Mahesh K B organization: MRC Clinical Trials Unit, University College London, London, U.K – sequence: 5 givenname: Patrick surname: Royston fullname: Royston, Patrick organization: MRC Clinical Trials Unit, University College London, London, U.K – sequence: 6 givenname: Abdel G surname: Babiker fullname: Babiker, Abdel G organization: MRC Clinical Trials Unit, University College London, London, U.K |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37155554$$D View this record in MEDLINE/PubMed |
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