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…

To conduct a multilevel meta-analysis of multiple single-case experimental design (SCED) studies, the individual participant data (IPD) can be analyzed in one or two stages. In the one-stage approach, a multilevel model is estimated based on the raw data. In the two-stage approach, an effect size is calculated for each participant and these effect…

The problem of assessing whether experimental results can be replicated is becoming increasingly important in many areas of science. It is often assumed that assessing replication is straightforward: All one needs to do is repeat the study and see whether the results of the original and replication studies agree. This article shows that the…

Methods for meta-analyzing single-case designs (SCDs) are needed to inform evidence-based practice in clinical and school settings and to draw broader and more defensible generalizations in areas where SCDs comprise a large part of the research base. The most widely used outcomes in single-case research are measures of behavior collected using…

The purpose this review was to conduct a meta-analysis of 25 years of mathematics interventions for students with mathematics difficulty or disability in grades 4 through 12. A search of the literature yielded 25 studies that met the inclusion criteria. Studies were coded to extract important study information (e.g., participant information,…