Parker Richard I, Hagan-Burke Shanna
Texas A&M University, College Station, USA.
Behav Modif. 2007 Nov;31(6):919-36. doi: 10.1177/0145445507303452.
This article takes a further look at the percentage of data points exceeding the median (PEM) analysis method for single-case research data, first presented in this journal by Hsen-Hsing Ma. Ma examined the relationship between PEM and the established percentage of nonoverlapping data (PND) and then applied PEM in a meta-analysis of 61 data sets, correlating their authors' judgments of intervention effectiveness with PEM. The present article covers PEM's historical and statistical context and then applies the new measure in a field test with 165 contrasts between a baseline phase A and a treatment phase B. For comparison, Pearson r , Kruskal-Wallis W, PND, and IRD (improvement rate difference) indices also are calculated and correlated with PEM, and all distributions are examined. Expert visual analysis ratings of the 165 graphs are correlated with all indices. PEM surpassed PND in its validation by other established measures. However, PEM was weaker in distribution shape and visual judgment validation. More strongly validated than either PEM or PND was the new nonparametric measure, IRD.
本文进一步探讨了单病例研究数据中超过中位数的数据点百分比(PEM)分析方法,该方法由马兴兴首次发表于本期刊。马研究了PEM与既定的非重叠数据百分比(PND)之间的关系,然后将PEM应用于对61个数据集的荟萃分析,将其作者对干预效果的判断与PEM进行关联。本文涵盖了PEM的历史和统计背景,然后在一项现场测试中应用这一新指标,该测试涉及基线A阶段和治疗B阶段之间的165组对比。为作比较,还计算了皮尔逊相关系数r、克鲁斯卡尔-沃利斯检验统计量W、PND和改善率差异(IRD)指标,并将它们与PEM进行关联,同时对所有分布进行了检验。对165张图表的专家视觉分析评分与所有指标进行了关联。在通过其他既定指标进行验证方面,PEM超过了PND。然而,PEM在分布形状和视觉判断验证方面表现较弱。新的非参数指标IRD比PEM或PND得到了更有力的验证。