Hierarchical linear modeling (HLM) has been recommended as a meta-analytic technique for the quantitative synthesis of single-case experimental design (SCED) studies. The HLM approach is flexible and can model a variety of different SCED data complexities, such as intervention heterogeneity. A major advantage of using HLM is that participant…

This study investigated the power of two-level hierarchical linear modeling (HLM) to explain variability in intervention effectiveness between participants in context of single-case experimental design (SCED) research. HLM is a flexible technique that allows the inclusion of participant characteristics (e.g., age, gender, and disability types) as…

In this study, we conducted a multilevel meta-analysis to determine whether the self-regulated strategy development (SRSD) approach to teaching writing to students with autism spectrum disorder (ASD) improves significantly the number of words written and overall quality of writing, whether the effects of SRSD were consistent or variable across…