A d-statistic for single-case designs that is equivalent to the usual between-groups d-statistic

A d-statistic for single-case designs that is equivalent to the usual between-groups d-statistic
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单案例设计的 d 统计量相当于通常的组间 d 统计量

DOI:
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发表时间:
2014
影响因子:
2.7
通讯作者:
J. L. Barrientos
J. L. Barrientos
中科院分区:
心理学3区
文献类型:
--
作者:
W. Shadish;L. Hedges;J. Pustejovsky;Jonathan G. Boyajian;K. J. Sullivan;A. Andrade;J. L. Barrientos

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我们描述了一种标准化的单例设计的平均差异统计量(D),它等同于组间实验中通常的d。我们展示了如何使用它来总结研究内病例的治疗效果,在规划新研究和拨款建议时进行权力分析,以及在同一问题的研究中进行荟萃分析效果。我们讨论了这种d-统计量的局限性,以及可能的补救措施。即便如此,与单例设计的其他效应大小测量方法相比,这种d-统计量在统计学上有更好的依据,而且与许多通用的线性模型方法(如多水平建模或广义相加模型)不同,它产生了标准化的效应大小,可以在不同结果测量的研究中进行整合。还提供了用于计算效果大小和功率分析的SPSS宏。
We describe a standardised mean difference statistic (d) for single-case designs that is equivalent to the usual d in between-groups experiments. We show how it can be used to summarise treatment effects over cases within a study, to do power analyses in planning new studies and grant proposals, and to meta-analyse effects across studies of the same question. We discuss limitations of this d-statistic, and possible remedies to them. Even so, this d-statistic is better founded statistically than other effect size measures for single-case design, and unlike many general linear model approaches such as multilevel modelling or generalised additive models, it produces a standardised effect size that can be integrated over studies with different outcome measures. SPSS macros for both effect size computation and power analysis are available.
DOI: --
发表时间: 2002
影响因子: --
作者:
Richards,Katherine;Singletary,Floris;Rothi,LeslieJGonzalez;Koehler,Shirley;Crosson,Bruce
通讯作者: Crosson,Bruce