ACCOMPLISHMENTS
Dr. Mariola Moeyaert is an expert methodologist in developing and validating statistical analysis techniques. She enhances the understanding of statistical data analysis techniques through funded research projects, international peer reviewed journal articles, applied illustrations, software demonstrations, and tutorials. She has published over 45 methodological and applied papers related to statistical analysis techniques in top tier international peer reviewed journals.
Here you can find a summary of Dr. Mariola Moeyaert’s current funded research projects:
FUNDING AGENCY
Institute of Education Sciences
PROJECT TITLE
Assessing Generalizability and variability of single-case design effect sizes using multilevel modeling including moderators
ROLE
Principal Investigator
BRIEF SUMMARY
The goal of this research project is to contribute to evidence-based decisions, research and practice in education through designing hierarchical linear modeling of single-case data (Shadish & Rindskopf, 2007). This project can be organized according to three specific aims: (1) the first aim is the empirical validation of the multilevel meta-analytic model including moderators in order to explain variability among effect sizes at the case and at the study level, (2) the second aim is the development and empirical validation of power calculations to detect meaningful moderator effects and (3) the last aim is evaluating current What Works Clearinghouse (WWC) standards for combining studies (including moderators) and making recommendations based on the results of the empirical validation in aim 1 and aim 2. The underlying rationale for this proposed grant is to respond to practical questions about how to design a multilevel meta-analysis that is powerful enough to generalize treatment effects and explain variability in treatment effects by including moderators.
FUNDING AGENCY
Institute of Education Sciences
PROJECT TITLE
Multilevel modeling of single-subject experimental data: Handling data and design complexities
ROLE
Co-Principal Investigator
BRIEF SUMMARY
Our research group was one of the first to propose, develop and promote the use of multilevel models to synthesize data across subjects, allowing for estimation of the mean treatment effect, variation in effects over subjects and studies, and subject and study characteristic moderator effects. The research that is proposed focuses on the multilevel modeling framework for the (meta-)analysis of single-case studies, both using raw data and effect sizes. We are looking at possible approaches for handling complexities, including (a) estimation of the variance components at the subject and study level, (b) heterogeneity in the covariance structure, (c) analysis of non-continuous outcome variables, (d) subject-specific external event effects, (e) response guided decisions, (f) complex functional forms, and (g) mixed designs
FUNDING AGENCY
Foundation for Child Development
PROJECT TITLE
Estimating the direct and indirect effects preschool teachers’ outreach efforts on children’s academic and socio-emotional outcomes during the transition to elementary school
ROLE
Consultant
BRIEF SUMMARY
In this project I estimate the direct and indirect effects of preschool teachers’ outreach efforts on children’s academic and socio-emotional outcomes during the transition to elementary school. I developed a moderated mediation model within the structural equation model framework to examine if these effects differ for children from economically disadvantaged backgrounds and whether these effects are mediated by way of increased parental involvement.
FUNDING AGENCY
Health Resources and Services Administration (HRSA)
PROJECT TITLE
Effects of Augmentative and Alternative Communication Interventions on Speech Production in Individuals with Autism Spectrum Disorders and other Developmental Disabilities: A Systematic Review and Meta-Analysis
ROLE
Consultant
BRIEF SUMMARY
The goal of this project is to conduct a systematic review and meta-analysis summarizing the effects of augmentative and alternative communication interventions on speech production in individuals with autism spectrum disorders and other developmental disabilities. I am (a) providing feedback on the selection of appropriate effect size metrics for single-case experimental designs including hierarchical linear modeling and design comparable effect size, and (b) implementing meta-analysis specific statistical analyses including sensitivity analyses and moderator analyses.