Internationally Renowned
Our expertise is obtained by working on grant funded research projects, collaborating with top tier research institutions, publishing in peer-reviewed journals with high impact factors and presenting at international conferences. In addition, Statistical Solutions Inc has more than 10 years' experience teaching basic and advanced statistical analysis courses.
ABOUT US
Mariola Moeyaert founded Statistical Solutions Inc. to provide consultancy services for basic and advanced statistical data analysis techniques. Data is everywhere and statistical techniques are a powerful tool to describe & summarize data, make predictions and make evidence-based data driven decisions. As an Associate Professor of Statistics, Ms. Moeyaert ensures that the latest reliable & valid data analytic techniques are used. Statistical Solutions Inc. offers several services including trainings and teachings, software demonstrations (e.g., SAS, R, SPSS, JMP, Matlab, Stata), interpreting software output, writing reports and publications, and providing one-on-one tutoring.
The specific research expertise of Ms. Moeyaert includes interrupted time series analysis, meta-analysis, advanced regression analysis and multilevel modeling. Click below to find more about her background, expertise and academic career:
SERVICES
Statistical Solutions Inc offers a variety of personalized services to individuals, corporations and public services in need of statistical data consultancy. We can provide the consultancy in person or through videoconferencing or email. All latest methodological and statistical innovations are incorporated in the service.
Clients can choose between the following three options:
-
Hourly statistical consultancy
-
Courses, lectures, workshops or webinars on specific statistical Topics
-
Software demonstrations
Hourly Statistical Consultancy
The hourly consultancy offered by Statistical Solutions Inc can take on multiple forms:
Designing
a powerful experimental study
Running
statistical analysis techniques
Selecting
the best statistical analysis technique to quantify and summarize data
Demonstrating
how to run statistical analyses techniques using statistical software packages
Interpreting and explaining
results obtained by running statistical analysis techniques
Reporting
the best statistical analysis technique to quantify and summarize data
Courses, Lectures, Workshops or Webinars on Specific Statistical Topics
Depending on the individual needs, Statistical Solutions can organize courses, lectures, workshops or webinars of varying lengths (one day, multiple days, weekly, semester lengths) and varying difficulty levels. Topics include descriptive statistics, basics of inferential statistics (one sample t-test, two-sample t-test, ANOVA, MANOVA, chi2 testing, etc.), regression analysis, meta-analysis, multilevel modeling, hierarchical linear modeling, single-case experimental design analysis, etc.
Software Demonstrations
Statistical Solutions can give software demonstrations in SAS, R, Stata, Jmp, SPSS, and MPlus. During the demonstrations, Statistical Solutions can use the client’s data depending on the client’s preference.
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 60 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.