Bulté Isis, Onghena Patrick
Katholieke Universiteit Leuven, Centre for Methodology of Educational Research, Leuven, Belgium.
Behav Res Methods. 2008 May;40(2):467-78. doi: 10.3758/brm.40.2.467.
Randomization tests are nonparametric statistical tests that obtain their validity by computationally mimicking the random assignment procedure that was used in the design phase of a study. Because randomization tests do not rely on a random sampling assumption, they can provide a better alternative than parametric statistical tests for analyzing data from single-case designs. In this article, an R package is described for use in designing single-case phase (AB, ABA, and ABAB) and alternation (completely randomized, alternating treatments, and randomized block) experiments, as well as for conducting statistical analyses on data gathered by means of such designs. The R code is presented in a step-by-step way, which at the same time clarifies the rationale behind single-case randomization tests.
随机化检验是非参数统计检验,通过在计算上模拟研究设计阶段所使用的随机分配程序来获得其有效性。由于随机化检验不依赖于随机抽样假设,因此对于分析单案例设计的数据,它们可以提供比参数统计检验更好的替代方法。本文介绍了一个R包,用于设计单案例阶段(AB、ABA和ABAB)和交替(完全随机、交替处理和随机区组)实验,以及对通过此类设计收集的数据进行统计分析。R代码以循序渐进的方式呈现,同时阐明了单案例随机化检验背后的基本原理。