Department of Psychology, Arizona State University7864, Tempe, AZ, USA.
Department of Medical Social Sciences, Northwestern University, 7864Chicago, IL.
Eval Health Prof. 2022 Mar;45(1):54-65. doi: 10.1177/01632787211070811. Epub 2022 Feb 25.
In response to the importance of individual-level effects, the purpose of this paper is to describe the new randomization permutation (RP) test for a mediation mechanism for a single subject. We extend seminal work on permutation tests for individual-level data by proposing a test for mediation for one person. The method requires random assignment to the levels of the treatment variable at each measurement occasion, and repeated measures of the mediator and outcome from one subject. If several assumptions are met, the process by which a treatment changes an outcome can be statistically evaluated for a single subject, using the permutation mediation test method and the permutation confidence interval method for residuals. A simulation study evaluated the statistical properties of the new method suggesting that at least eight repeated measures are needed to control Type I error rates and larger sample sizes are needed for power approaching .8 even for large effects. The RP mediation test is a promising method for elucidating intraindividual processes of change that may inform personalized medicine and tailoring of process-based treatments for one subject.
为了凸显个体水平效应的重要性,本文旨在描述一种新的随机化置换(RP)检验方法,用于检验单一被试的中介机制。我们通过为单人提出一种中介检验方法,对个体水平数据的置换检验进行了扩展。该方法要求在每个测量时刻对处理变量的水平进行随机分配,并对一个被试的中介变量和结果进行重复测量。如果满足几个假设条件,则可以使用置换中介检验方法和残差置换置信区间方法,对一个被试的治疗如何改变结果的过程进行统计学评估。一项模拟研究评估了新方法的统计性质,结果表明,至少需要 8 次重复测量来控制 I 型错误率,并且即使对于大效应,也需要更大的样本量来接近 80%的功效。RP 中介检验是一种很有前途的方法,可以阐明个体内部的变化过程,从而为个体化医学和基于过程的单一被试治疗的定制提供信息。