Using AB Designs With Nonoverlap Effect Size Measures to Support Clinical Decision-Making: A Monte Carlo Validation.

Using AB Designs With Nonoverlap Effect Size Measures to Support Clinical Decision-Making: A Monte Carlo Validation. Behav Modif. 2019 Jul 13;:145445519860219 Authors: Giannakakos AR, Lanovaz MJ Abstract Single-case experimental designs often require extended baselines or the withdrawal of treatment, which may not be feasible or ethical in some practical settings. The quasi-experimental AB design is a potential alternative, but more research is needed on its validity. The purpose of our study was to examine the validity of using nonoverlap measures of effect size to detect changes in AB designs using simulated data. In our analyses, we determined thresholds for three effect size measures beyond which the type I error rate would remain below 0.05 and then examined whether using these thresholds would provide sufficient power. Overall, our analyses show that some effect size measures may provide adequate control over type I error rate and sufficient power when analyzing data from AB designs. In sum, our results suggest that practitioners may use quasi-experimental AB designs in combination with effect size to rigorously assess progress in practice. PMID: 31303024 [PubMed - as supplied by publisher]
Source: Behavior Modification - Category: Psychiatry & Psychology Authors: Tags: Behav Modif Source Type: research