Evaluating Intervention Effects in Single-Case Research Designs
Evaluating Intervention Effects in Single-Case Research Designs
复制标题
DOI：
10.1002/jcad.12038
复制
发表时间：
2015-10-01
影响因子：
2.3
通讯作者：
Ninci, Jennifer
中科院分区：
文献类型：
--
作者：
Vannest, Kimberly J.;Ninci, Jennifer
单一病例研究设计主要依赖于视觉分析来确定治疗效果。然而，目前对循证治疗的关注引起了新方法的发展。本文介绍了5个效应量指标的描述、计算、优点和缺点，以及解释指南：非重叠数据的百分比、超过中位数的数据的百分比、改善率差、所有对的非重叠和Tau-U。
Single-case research designs have primarily relied on visual analysis for determining treatment effects. However, current foci on evidence-based treatment have given rise to the development of new methods. This article presents descriptions, calculations, strengths and weaknesses, and interpretative guidelines for 5 effect size indices: the percent of nonoverlapping data, the percent of data exceeding the median, improvement rate difference, nonoverlap of all pairs, and Tau-U.