Moeyaert Awarded IES Early Career Award to Develop Advanced Statistical Methodologies

Albany, NY (June 6, 2019) – Dr. Mariola Moeyaert, assistant professor in Educational Counseling & Psychology, received an Early Career Award from the Institute of Education Sciences (IES), part of the United States Department of Education. The project, titled Assessing Generalizability and Variability of Single-Case Design Effect Sizes using Multilevel Modeling Including Moderators, is a two-year award in the amount of $224,998.

The Early Career Awards in Statistical and Research Methodology in Education are highly competitive with only nine prior projects being funded since 2014. The Stats/Methods program is also unique among IES initiatives. “Most grant competitions held by IES are intended to support research that directly affects students and/or teachers in the classroom. The field also needs to advance in terms of how research is conducted. Through the Stats/Methods program, grantees conduct research that helps applied researchers address challenges often encountered in education research...,” according to the IES website.

The project will uncover innovative methods that can be used to quantitatively summarize small-N studies such as single-case experimental design (SCED) studies. SCED studies are unique in that a limited number of subjects are studied in-depth repeatedly over time to assess whether there is a causal relation between the introduction of an intervention and the change in a dependent variable.

As a result of their usefulness, SCEDs are very popular in a variety of research fields including speech-language pathology, education, technology-based medical interventions, rehabilitation, and more. Because of the popularity of SCED studies within and across a variety of different research fields, a large number of SCED data is available for quantitative synthesis. The IES early career award will contribute significantly to evidence-based research, theory and practice by accumulating this scientific knowledge using multilevel meta-analytic modeling.

Over the course of two years, Dr. Moeyaert will be using secondary data (for empirical demonstrations) and large-scale Monte Carlo simulation studies (investigating the statistical properties) that will help guide the design of a powerful multilevel meta-analysis. The focus is specifically on moderator effects in order to explain variability among effect sizes at the subject and at the study level. Estimating and explaining variability in effect sizes is important in the context of SCEDs because applied SCED researchers, practitioners and policy makers are not only interested in overall average treatment effect estimates across subjects and across studies, but also whether the treatment works for all subjects.

“The School of Education is proud to be the home of renowned faculty who not only conduct research on a range of questions in education and human development fields; but also advancing the very ways that such research is conducted,” commented the School of Education’s Interim Dean, Jason E. Lane. “Professor Moeyaert is a national leader in the development of advanced research methodologies; identifying new and cutting-edge ways of conducting research in a range of fields.”