Meta-analytic techniques can be used to aggregate evaluation results across studies. In the case of single-subject research designs, we could combine findings from evaluations with 5, 10 or 20 clients to determine, on average, how effective an intervention is. This is a more complex and sophisticated way of understanding differences across studies than reporting those changes qualitatively or simply reporting the individual effect sizes for each study. In this chapter, the authors discuss why meta-analysis is important to consider in single-subject research, particularly in the context of building research evidence. They then demonstrate how to do this using SSD for R functions. Building upon effect sizes, introduced in Chapter 4, the authors illustrate the conditions under which it is appropriate to use traditional effect sizes to conduct meta-analyses, how to introduce intervening variables, and how to evaluate statistical output. Additionally, the authors discuss and illustrate the computation and interpretation of a mean Non-Overlap of All Pairs in situations which traditional effect sizes cannot be used.
Reading Interventions for Improving Phonological Awareness and Word Recognition of Students With Disabilities: A Meta-Analysis of Single-Subject Research Designs
