Amsterdam, Netherlands

How to Conduct a Meta-Analysis Using Open-Science Software

online course
when 20 July 2020 - 31 July 2020
language English
duration 2 weeks
credits 3 EC
fee EUR 500

With the increasing use of alternative software packages like R in data analysis, now is the time to learn their ins and outs. The large number of active programmers creating R packages makes this an up-to-date programme providing a huge range of statistical analyses. Researchers also use R to write functions for analysing data, or to create professional plots.

“Systematic reviews and meta-analyses are essential tools for summarizing evidence accurately and reliably (…)” (Liberati et al., p. 1). Currently, meta-analysis is a widely applied technique. It applies to many of today’s issues surrounding scientific research. It can be used not only to reach conclusions regarding the overall effect of proven correlation, but it is also essential for finding and estimating publication bias. The meta-analysis is also useful when conducting a priori power analysis to design sample size.

During this course, students will learn how to formulate a problem and analyze it conducting a meta-analysis in JASP, an open-science software. Also, students will practice a wide-and-far literature search and will learn how to report their findings following the PRISMA standards. Students will learn the basics of how to prepare and describe a meta-analytical study in a separate article. They will see how to apply this technique to summarise studies found in a manuscript in order to improve the cohesion and “publishability.”

This course is taught in the form of an interactive seminar, in which students will complete four individual assignments, one each day. After submission of each assignment, students will receive feedback.

There will be discussions on the following topics:

- Two types of systematic reviews
- Open science and meta-analysis: multisite replications
- Pros and cons of meta-analysis
- Publication bias and quality of publications
- Effect size and how to calculate it
- Literature search, exclusion, inclusion, and coding
- Heterogeneity and its consequences
- Available software, including JASP
- Fixed- and random-effects model
- Estimating overall effect size
- Analysis of moderators

Additionally, students will become familiar with examples of published research to learn more about how to analyse them.

Course leader

Dr. Jacek Buczny

Target group

This course is for Advanced Bachelor’s and Master’s students. However, enthusiastic PhD candidates and professionals interested in the application of quantitative data analysis are also very welcome to register for this summer course. This course takes inspiration from the disciplines of economics and business studies, as well as social and behavioral sciences. If you have doubts about your eligibility for the course, please let us know. Our courses are multi-disciplinary and therefore open to students and professionals with a wide variety of backgrounds.

Course aim

Upon completion of the course, the student should be able to:

- Formulate a research question to conduct a meta-analysis
- Carry out a literature search far and wide
- Systematically review relevant literature
- Code studies fitting inclusion criteria
- Meta-analyze the coded effects using JASP software
- Interpret and report the meta-analytic results

Credits info

3 EC
Contact Hours: 45
Do you want to make the most out of your summer? You can combine this course with a course in session 1 to create a 4-week Online Summer School.

Fee info

EUR 500: The tuition fee for a two-week online course is €500. This tuition fee includes:

•Two week online course
•Exclusive content for a limited number of students
•Transcript of records with a maximum of 3 ECTS (European study credits)
•Certificate of attendance after completing the course
•Individual/group guidance from professor
•Interactive classes
•Full support from the summer school team
•Optional (virtual) social programme