Standardized Mean Difference for Single-Case Designs
The between-case standardized mean difference is an effect-size measure that puts the result of a single-case experiment on the same numerical scale as Cohen's d from a conventional between-groups study, so that single-case and group findings can be combined in the same meta-analysis. Developed by Larry Hedges, James Pustejovsky, and William Shadish in 2012, it solves a long-standing problem: the many ad hoc nonoverlap indices used in single-case research (PND, PAND, IRD, Tau-U) are not comparable in scale to the standardized mean differences that dominate the broader evidence-synthesis literature. Their estimator models the single-case data with a hierarchical model that separates within-case variation from between-case variation, then standardizes the estimated treatment effect by the total standard deviation — the same denominator a between-subjects d would use. A 2013 extension specialized the estimator to multiple-baseline designs across individuals. The result is a design-comparable effect size with a known variance, suitable for disability and special-education research where single-case studies are abundant.
רשומת מקור
ציטוטים הועתקו מילה במילה מרשומת המקור של המתודה. לא מוסקת כל אימות ברמת הטענה מהם.
- Hedges, L. V., Pustejovsky, J. E., & Shadish, W. R. (2012). A standardized mean difference effect size for single case designs. Research Synthesis Methods, 3(3), 224-239. · DOI 10.1002/jrsm.1052
- Hedges, L. V., Pustejovsky, J. E., & Shadish, W. R. (2013). A standardized mean difference effect size for multiple baseline designs across individuals. Research Synthesis Methods, 4(4), 324-341. · DOI 10.1002/jrsm.1086
טענות מאוצרות
טענות שנשמרו ביומן הראיות, לכל אחת הערכה משלה.
תצוגה זו אינה ממציאה הערכת טענה כאשר ליומן אין אחת.
מתודות קשורות
נוצר מגרף המתודות ומוצג כיחסים שהוצעו על ידי המכונה — לא מוסקת כל טענת ראיה.