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…

This study introduces an innovative meta-analytic approach, two-stage multilevel meta-analysis that considers the hierarchical structure of single-case experimental design (SCED) data. This approach is unique as it is suitable to include moderators at the intervention level, participant level, and study level, and is therefore especially…

The focus of the current study is on handling the dependence among multiple regression coefficients representing the treatment effects when meta-analyzing data from single-case experimental studies. We compare the results when applying three different multilevel meta-analytic models (i.e., a univariate multilevel model avoiding the dependence, a…

Multisite research (MSR) offers the key advantages of greater statistical power and external validity via larger and more diverse participant pools. In second language acquisition (SLA) research, recent developments in meta-analysis have created a robust foundation for MSR. Although logistical and financial obstacles can complicate expansion…

Single-case designs are a class of research designs for evaluating intervention effects on individual cases. The designs are widely applied in certain fields, including special education, school psychology, clinical psychology, social work, and applied behavior analysis. The multiple baseline design (MBD) is the most frequently used single-case…

One approach for combining single-case data involves use of multilevel modeling. In this article, the authors use a Monte Carlo simulation study to inform applied researchers under which realistic conditions the three-level model is appropriate. The authors vary the value of the immediate treatment effect and the treatment's effect on the time…

The purpose of this article is to demonstrate how hierarchical linear modeling (HLM) can be used to enhance visual analysis of single-case research (SCR) designs. First, the authors demonstrated the use of growth modeling via HLM to augment visual analysis of a sophisticated single-case study. Data were used from a delayed multiple baseline…

This meta-analysis used hierarchical linear modeling to examine 115 single-case studies with 343 participants that examined the effectiveness of social skills interventions for individuals with autism spectrum disorder (ASD). The average effect size of the included studies was 1.40 (SD = 0.43, 95% CL = 1.32-1.48, N = 115). In the further, several…