Mariola Moeyart

Mariola Moeyaert

Multilevel analysis, meta-analysis, single-case experimental data, Bayesian statistics, bootstrapping, structural equation modeling, longitudinal data analysis, and international comparative research.

The World Within Reach
Mariola Moeyaert, Ph.D.
Assistant Professor
 

School of Education
Department: Educational and Counseling Psychology

Division of Educational Psychology and Methodology
Address:
ED 231
Phone:
518-442-5050

 

Introduction

Dr. Mariola Moeyaert joined the faculty of Educational Psychology and Methodology in the Fall of 2015. She received her PhD from the Katholieke Universiteit Leuven (KU Leuven) in Belgium and worked as a Postdoctoral fellow at the Center of Advanced Study in Education at the City University of New York. Her major research interests and publications are in the field of multilevel analysis, meta-analysis and single-case experimental data. She is also interested in Bayesian statistics, bootstrapping, structural equation modeling, longitudinal data analysis, and international comparative research. She (co)authored about 20 international publications, in such journals as Psychological Methods, Mutlivariate Behavior Research, Journal of School Psychology, Behavior Research Methods, School Psychology Quarterly, etc., reporting about developments in research methodology (including several extensive simulation studies) and about applications of statistical models on educational data. Currently, she is involved as Co-PI in a research project funded by the Institute of Educational Sciences titled “Multilevel Modeling of single-subject experimental data: Handling data and design complexities”.

Additional Information

Publications

Joo, S., Ferron, J., Moeyaert, M., Beretvas, S. N., & Van den Noortgate, W. (2018). The Impact of Response-Guided Baseline Phase Extensions on Treatment Effect Estimates. Invited for special issue in Research in Developmental Disabilities. 10.1016/j.ridd.2017.12.018 (IF = 1.630)

Joo, S., Ferron, J., Moeyaert, M., Beretvas, S., & Van den Noortgate, W. (2017). Approaches for Specifying the Level-1 Error Structure when Synthesizing Single-Case Data. Journal of Experimental Education. https://doi.org/10.1080/00220973.2017.1409181 (IF = 1.64)

Lobo, M. Moeyaert, M., Babik. I., & Cunha, A. (2017). Single-case experimental designs for complex neurological disorders. Journal of Neurologic Physical Therapy, 14, 187-197. (IF = 1.77)

Moeyaert, M., Rindskopf, D., Onghena, P., & Van den Noortgate, W. (2017). Hierarchical linear modeling of single-case data: A comparison of Maximum Likelihood and Bayesian estimation. Psychological Methods. Advance online publication. http://dx.doi.org/10.1037/met0000136 (IF = 9.46)

Klingbeil, D., Moeyaert, M., Archerm C., Chimnoza, T. M., & Zwolski, S. A. (2017). Examining the efficacy of peer-mediated incremental rehearsal. School Psychology Review, 46, 122-140. (IF = 2.59)

Manolov, R., & Moeyaert, M. (2017). Recommendations for choosing single-case data analytical techniques. Behavior Therapy, 48, 97-114. doi: 10.1016/j.beth.2016.04.008 (IF = 4.33)

Moeyaert, M., Ugille, M., Beretvas, S., Ferron, J., & Van Den Noortgate, W. (2016). Methods for dealing with multiple outcomes in meta-analysis: a comparison between averaging effect sizes, robust variance estimation and multilevel meta-analysis. International Journal of Social Research Methodology. doi. 10.1080/13645579.2016.1252189 (IF = 1.42)

Manolov, R., & Moeyaert, M. (2016). How can single-case data be analyzed? Software resources, tutorial, and reflections on analysis. Behavior Modification, 41,179-228. doi: 10.1177/0145445516664307 (IF = 1.22)

Moeyaert, M., Brosnan, J., Brooks, K., Healy, O., Heyvaert, M., Onghena, P., & Van den Noortgate, W. (2016). Multilevel analysis of multiple-baseline data evaluating precision teaching as an intervention for improving fluency in foundational reading skills for at risk readers. Exceptionality. doi: 10.1080/09362835.2016.1238378 (IF = 0.95)

Recent and Forthcoming Research Presentations (*student coauthors)

Moeyaert, M. &* Rodabaugh, E. (2018, August). Multilevel meta-analysis of single-case experimental data: Bayesian estimation. APA Convention, San Francisco, CA.

Moeyaert, M., Beretvas, *Zhang, & *Rodabaugh, E. (2018, May). Bayesian model averaging for single-case experimental design effect size estimation. Modern Modeling Conference. Storrs, Connecticut.

*Akhmedjanova, D., & Moeyaert, M. (2018, May). Power estimates to test predictor effects in two-level modeling of single-case data. Modern Modeling Conference. Storrs, Connecticut.

Moeyaert, M., Beretvas, S.N., *Rodabaugh, E., Ferron, J., & Van den Noortgate, W. (2018, March). How to improve Bayesian estimation when synthesizing single-case experimental design studies’ random effects variance components? S4 conference – Small Sample Size Solutions. Utrecht, the Netherlands.

Awards and Honors

Dr. Mariola Moeyaert, received the 2016 Anastasi Dissertation Award from Division 5 of the American Psychological Association for her dissertation, “Three-level synthesis of single-subject experimental data: Further developments, empirical validation and applications."