Faculty of Psychology and Educational Sciences, University of Leuven, Vesaliusstraat 2, 3000, Leuven, Belgium,
Behav Res Methods. 2012 Dec;44(4):1244-54. doi: 10.3758/s13428-012-0213-1.
One way to combine data from single-subject experimental design studies is by performing a multilevel meta-analysis, with unstandardized or standardized regression coefficients as the effect size metrics. This study evaluates the performance of this approach. The results indicate that a multilevel meta-analysis of unstandardized effect sizes results in good estimates of the effect. The multilevel meta-analysis of standardized effect sizes, on the other hand, is suitable only when the number of measurement occasions for each subject is 20 or more. The effect of the treatment on the intercept is estimated with enough power when the studies are homogeneous or when the number of studies is large; the power of the effect on the slope is estimated with enough power only when the number of studies and the number of measurement occasions are large.
一种将单组实验设计研究数据合并的方法是进行多层次元分析，以未标准化或标准化回归系数作为效应量指标。本研究评估了这种方法的性能。结果表明，对未标准化效应量进行多层次元分析可以得到良好的效应估计。另一方面，只有当每个被试的测量次数为 20 次或更多时，标准化效应量的多层次元分析才适用。当研究同质或研究数量较大时，治疗对截距的影响具有足够的估计效力；只有当研究数量和测量次数较大时，对斜率的影响才具有足够的估计效力。
