artcat: Sample-size calculation for an ordered categorical outcome

被引:3
|
作者
White, Ian R. [1 ]
Marley-Zagar, Ella [1 ]
Morris, Tim P. [1 ]
Parmar, Mahesh K. B. [1 ]
Royston, Patrick [1 ]
Babiker, Abdel G. [1 ]
机构
[1] UCL, MRC Clin Trials Unit, London, England
来源
STATA JOURNAL | 2023年 / 23卷 / 01期
基金
英国医学研究理事会;
关键词
st0700; artcat; sample size; power; clinical trial; randomized controlled trial; noninferiority trial; substantial-superiority trial; categorical variable; proportional-odds model; evaluation; CLINICAL-TRIALS; SURVIVAL; MULTIARM; EVENTS; POWER;
D O I
10.1177/1536867X231161934
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
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.
引用
收藏
页码:3 / 23
页数:21
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