Multilevel modeling (MLM) is an approach for meta-analyzing single-case experimental designs (SCED). In this paper, we provide a step-by-step guideline for using the MLM to meta-analyze SCED time-series data. The MLM approach is first presented using a basic three-level model, then gradually extended to represent more realistic situations of SCED data, such as modeling a time variable, moderators representing different design types and multiple outcomes, and heterogeneous within-case variance. The presented approach is then illustrated using real SCED data. Practical recommendations using the MLM approach are also provided for applied researchers based on the current methodological literature. Available free and commercial software programs to meta-analyze SCED data are also introduced, along with several hands-on software codes for applied researchers to implement their own studies. Potential advantages and limitations of using the MLM approach to meta-analyzing SCED are discussed.
- Three-level Analysis
- Single-case Experimental Design
- Multilevel Modeling