首页 | 本学科首页   官方微博 | 高级检索  
     检索      


A Permutation Solution to Test for Treatment Effects in Alternation Design Single-Case Experiments
Authors:Francesca Solmi  Patrick Onghena  Luigi Salmaso  Isis Bulté
Institution:1. Department of Statistics , University of Padova , Padova , Italy;2. Faculty of Psychology and Educational Sciences , Katholieke Universiteit of Leuven , Leuven , Belgium;3. Department of Management and Engineering , University of Padova , Vicenza , Italy
Abstract:Research involving a clinical intervention is normally aimed at testing the treatment effects on a dependent variable, which is assumed to be a relevant indicator of health or quality-of-life status. In much clinical research large-n trials are in fact impractical because the availability of individuals within well-defined categories is limited in this application field. This makes it more and more important to concentrate on single-case experiments. The goal with these is to investigate the presence of a difference in the effect of the treatments considered in the study. In this setting, valid inference generally cannot be made using the parametric statistical procedures that are typically used for the analysis of clinical trials and other large-n designs. Hence, nonparametric tools can be a valid alternative to analyze this kind of data. We propose a permutation solution to assess treatment effects in single-case experiments within alternation designs. An extension to the case of more than two treatments is also presented. A simulation study shows that the approach is both reliable under the null hypothesis and powerful under the alternative, and that it improves the performance of a considered competitor. In the end, we present the results of a real case application.
Keywords:Permutation test  Power comparison  Single-case experiment  Time process
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号