The relationship between visual analysis and five statistical analyses in a simple AB single-case research design
The relationship between visual analysis and five statistical analyses in a simple AB single-case research design
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DOI：
10.1177/0145445503261167
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发表时间：
2006-09-01
影响因子：
2.3
通讯作者：
Mahadevan, Lakshmi
中科院分区：
文献类型：
--
作者：
Brossart, Daniel F.;Parker, Richard I.;Mahadevan, Lakshmi
本研究探讨了一些实际问题的单例研究人员谁依赖于图形数据的可视化分析，但谁也可以考虑补充使用有前途的统计分析技术。该研究试图回答三个主要问题：（a）这些分析技术对“有效干预”数据的典型效应量范围是什么？(b)这些相同分析技术的结果与基于视觉分析的有效干预判断的一致程度如何？和（c）自相关在解释这些分析结果中起什么作用？为了回答这些问题，五个分析技术进行了比较，45名博士生和教师的判断，他们从35个制造AB设计图的视觉分析评估干预效果。研究人员和从业人员使用单例设计的影响进行了讨论。
This study explored some practical issues for single-case researchers who rely on visual analysis of graphed data, but who also may consider supplemental use of promising statistical analysis techniques. The study sought to answer three major questions: (a) What is a typical range of effect sizes from these analytic techniques for data from "effective interventions"? (b) How closely do results from these same analytic techniques concur with visual-analysis-basedjudgments of effective interventions? and (c) What role does autocorrelation play in interpretation of these analytic results? To answer these questions, five analytic techniques were compared with the judgments of 45 doctoral students and faculty, who rated intervention effectiveness from visual analysis of 35 fabricated AB design graphs. Implications for researchers and practitioners using single-case designs are discussed.