A 5-hour workshop taught by Mariola Moeyaert, Ph.D.

Overview

This is the second of two 5-hour workshops on meta-analysis. Sign up for Part 1 here.

Meta-analysis is used to: combine evidence across different research studies; integrate multiple studies into a single statistical framework; yield more precise estimates of effect sizes; allow for unique treatment comparisons; explain differences arising from conflicting study results; and identify areas for future research.  Meta-analytic methods are employed in a diverse array of disciplines across the social, behavioral, health, and agricultural sciences.

This 2-day workshop provides hands-on exposure to the process involved in conducting a meta-analysis from the planning stage, through the selection of appropriate statistical techniques, through the issues involved in analyzing data, to the interpretation of results. Examples and case studies from the social sciences will be integrated into the discussions and lectures. The instructor will share detailed content slides, practice data sets, and annotated code with the participants.

Note: Lecture examples and demonstrations will rely on free software: Excel, the R Statistical Computing Environment, and specific software for meta-analysis (RevMan). Meta-analysis techniques are also available and easily accessible in other major software packages (e.g., Stata, SAS, and SPSS). The instructor can provide the students with Stata, SAS, and SPSS syntax upon request.

Expected outcomes

During the workshop, the participants will learn how to formulate an appropriate meta-analytic research question that can be assessed by synthesizing studies’ estimates of one of the effect sizes. The participants will have the opportunity to conduct a small systematic literature search and select primary studies eligible for inclusion. Data from these studies will be retrieved, coded, and synthesized using a fixed effect and a random effects meta-analytic model. The participants will learn how to calculate various kinds of effect sizes and to use them to conduct and make appropriate inferences from meta-analyses. Participants will have the opportunity to work on a mini meta-analysis project, using data provided by the instructor.

Pricing and schedule

Day 1: Thursday, March 10, 11AM to 4PM (EST)
Day 2: Friday, March 11, 11AM to 4PM (EST)
Cost: $225 for one day ($400 for 2 days with multiple workshop discount. Email to request discount code.)
Location: Online

We offer $50 discounts for graduate students and $25 discounts for multiple workshop enrollments. Find out about our discounts here.

The main workshop material is scheduled for 10 hours, divided over 2 days. Time permitting, Dr. Moeyaert will answer questions about participants’ specific research projects. Participants can ask questions via chat, microphone, or telephone. In order to allow sufficient time for questions, the number of workshop participants is limited to 30.

Who should attend?

Researchers interested in conducting a meta-analysis.

Agenda

Part 2 of the meta-analysis process – data analysis

• Step 7. Fixed effect versus random effect meta-analysis
• Step 8. Moderator analysis (subgroup analysis and meta-regression)

Part 3 of the meta-analysis process – discussing and reporting the results

• Step 9. Interpretation of the results
• Step 10. Reporting the results.

About the instructor

Dr. Mariola Moeyaert is an Associate Professor Statistics within the division of Educational Psychology and Methodology at UAlbany. She received her PhD in Educational Statistics 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 interrupted time series analysis. She is also interested in Bayesian statistics, bootstrapping, structural equation modeling, longitudinal data analysis, and international comparative research. She (co)authored about 47 international publications, in such journals as Psychological Methods, Multivariate Behavior Research, Journal of School Psychology, Behavior Research Methods, School Psychology Quarterly, etc., reporting about developments in research methodology (including several computing intensive Monte Carlo simulation studies) and about applications of statistical models on educational/medical data. Currently, she is involved as PI and Co-PI in research projects funded by the Institute of Education Sciences about methodological advancements in the field of multilevel meta-analysis. You can find more information about Dr. Mariola Moeyaert by following these two links:

(1) https://www.statisticalsolutionsinc.com/ (personal website)  and

(2) https://www.albany.edu/education/faculty/mariola-moeyaert (University at Albany website).