Gladwin Thomas Edward
Department of Psychology and Counseling, University of Chichester, Chichester, United Kingdom.
Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, the Netherlands.
MethodsX. 2020 Jun 2;7:100947. doi: 10.1016/j.mex.2020.100947. eCollection 2020.
The paper presents the details of an implementation of repeated measures ANOVA, consisting of a set of functions to organize data and represent contrasts to be tested and run statistical tests. The implementation is focused on uses common in experimental psychology. An arbitrary number of within-subject factors, each with an arbitrary number of levels, can be used. A non-parametric, randomization- and permutation-based formulation of repeated measures ANOVA was defined and implemented. Methods for testing interactions with categorical and continuous between-subject variables are implemented. Post-hoc tests for exploring interactions are automated. Simulations indicate correct control of false positive rate for all types of test. The software provides output with statistics including -values and partial eta squared.-An open source implementation of repeated measures ANOVA based on effect coding.-Generates -values and automatized unpacking of interactions for N-factor designs.-A non-parametric test is defined based on permutation tests.
本文介绍了重复测量方差分析的实现细节，包括一组用于组织数据、表示待检验对比以及运行统计检验的函数。该实现主要针对实验心理学中的常见用途。可以使用任意数量的被试内因素，每个因素又可以有任意数量的水平。定义并实现了基于随机化和排列的非参数重复测量方差分析公式。实现了用于检验与分类和连续被试间变量交互作用的方法。探索交互作用的事后检验是自动化的。模拟表明对所有类型的检验都能正确控制假阳性率。该软件提供包含p值和偏 eta 平方等统计量的输出。 - 基于效应编码的重复测量方差分析的开源实现。 - 为N因素设计生成p值并自动分解交互作用。 - 基于排列检验定义了非参数检验。
