Authors: Manolov, Onghena & Van den Noorgate (2021)
The authors of the article suggest that multi-level models can be used to include data from alternating treatments and changing criterion designs in meta-analyses of single-case experimental designs. They argue that these designs are underrepresented in current meta-analyses and that their exclusion can lead to a biased representation of the evidence. The article highlights the need for careful consideration of sample size and missing data when using multi-level models for meta-analysis of single-case designs. The authors argue that multi-level models can be a useful tool for including data from a wider range of single-case designs in meta-analyses, providing a more comprehensive and accurate representation of the evidence.
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Full reference: Manolov, R., Onghena, P., & Van den Noortgate, W. (2022). Meta-analysis of single-case experimental designs: How can alternating treatments and changing criterion designs be included?. Evidence-Based Communication Assessment and Intervention, 1-28.