Dr. Mariola Moeyaert presented our first Brown Bag discussion of the semester. Dr. Moeyaert discussed the topic of "Multilevel Meta-Analysis of Single-Case Effect Size Estimators: General Introduction and Application".
This is Dr. Moeyaert's first year teaching at UAlbany. She is teaching Statistics 1 this Fall and will be teaching Statistics 2 and Single-Case Experimental Design in the Spring of 2016. Dr. Moeyaert received her Ph.D. in Educational Statistics at the Methodology of Educational Sciences Research Group, KU Leuven, Belgium.
Dr. Moeyaert has been researching how the three-level meta-analytic model can be used to combine data from single-subject experimental designs and estimate effect size. The findings can be used to evaluate and improve interventions in addition to influencing future single-subject experimental design research.
The multi-level analysis of single-case experimental data consists of three main parts: single-case experimental designs, multilevel modeling, and meta-analysis. Single-case experimental designs are used to collect data for a single individual over time. The collected data are used to determine if an intervention is having an impact on an individual's performance on what is being measured. A multilevel modeling approach allows researchers to look at the effect sizes within cases, across multiple cases, and across multiple studies. Meta-analysis is then used to determine if interventions are useful and successful. Dr. Moeyaert's research has concluded that a multilevel modeling framework successfully estimates the effect within cases, across cases, and across studies. 
