Answers are grounded in this paper and cite their sources.
The identification of evidence-based practices continues to provoke issues of disagreement across multiple fields. One area of contention is the role of single-subject design (SSD) research in providing scientific evidence. The debate about SSD’s utility centers on three issues: sample size, effect size, and serial dependence. One potential method for addressing all three issues is hierarchical linear modeling (HLM) meta-analysis. This study explored the utility of HLM meta-analysis of SSD. A total of 206 functional behavior assessment–based intervention outcome graphs were aggregated to assess whether HLM meta-analysis could identify (a) an overall effect size and statistical significance for mean shift, slope, and variability; (b) how the results mapped to two additional effect size calculations; and (c) whether the procedure met SSD synthesis criteria outlined by Wolery, Busick, Reichow, and Barton.
No takes yet. Share an insight, caveat, or question.
Gage et al. (2012) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: