Individual Participant Data Meta-Analysis Including Moderators: Empirical Validation

Abstract

We have entered an era in which scientific evidence increasingly informs research practice and policy. As there is an exponential increase in the use of single-case experimental designs (SCEDs) to evaluate intervention effectiveness, there is accumulating evidence available for quantitative synthesis. Consequently, there is a growing interest in techniques suitable to meta-analyze SCED research. One technique that can be applied is individual patient data (IPD) meta-analysis. IPD is a flexible approach, allowing for a variety of modeling options such as modeling moderators to explain intervention heterogeneity. To date, no methodological research has been conducted to evaluate the statistical properties of effect estimates obtained by using IPD meta-analysis with the inclusion of moderators. This study is designed to address this by conducting a large-scale Monte Carlo study. Based on the results, specific recommendations are provided to indicate under which conditions the IPD meta-analysis including moderators is suitable.

Keywords:

• Individual patient meta-analysis
• meta-analysis
• moderators
• Monte Carlo simulation study
• simulation studies
• single-case experimental design

Author contributions

The content is solely the responsibility of the author and does not necessarily represent the official views of the Institute of Education Sciences, or the U.S. Department of Education.

Additional information

Funding

This research was supported by the Institute of Education Sciences, U.S. Department of Education, through grant R305D190022.