In all disciplines within management research, numerous relationships (effects of some X on a specific Y) have been studied multiple times, and summarizing the existing empirical findings may result in an important scientific contribution. For example, one could determine the overall effect of a particular marketing instrument (price, advertising, etc.) on sales and whether the effect depends on market characteristics, study design, or other moderators. Meta-analysis encompasses a broad set of methods to conduct a systematic, quantitative review of the literature in order to derive empirical generalizations. As such, conducting a meta-analysis is an excellent project for a PhD student or other (junior) researcher having to review the literature on a particular topic.
This workshop will deal with methods for conducting a meta-analysis. The purpose is to train the participants to conduct and publish a high-quality scientific meta-analysis within the broad field of management research. The seminar will cover the entire meta-analysis research process, from problem formulation, literature search, coding of the effects, analysis, to reporting and publishing the findings.
The emphasis is on knowledge and skills needed to conduct a meta-analysis, not only on the statistical details. All steps of the meta-analysis process (including the statistical analyses) will be demonstrated and practiced in assignments during the workshop. In addition, all topics will be illustrated by means of actual meta-analysis examples. Participants will be informed about relevant literature (textbooks and journal articles) and software supporting meta-analysis projects. In particular, most analyses will be demonstrated using R; in particular the package metafor.
Assignments: multiple assignments (six) on the various steps in the meta-analysis process.
Exam Attendance, active participation, presentations, and successful finishing the assignments.
Credits: 6 ECT
This workshop contains lecture-type sessions and sessions in which participants can practice and work on assignments.
Prerequisites: Knowledge of basic statistical methods like t-tests and regression analysis is essential. Experience with the software package R would be very helpful. If a participant has no experience at all with R, it is highly recommended to take a course (e.g. on-line by Datacamp.com), read a textbook , or otherwise learn the basics of working with R.
Programme Schedule (including start and end time): This is a four-day workshop, with sessions 09.00-12.00 and 13.00-16.00 (with a short break in both sessions, and lunch 12.00-13.00) each day; except that the session on Friday afternoon ends around 14.00.
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Registration Deadline: September 19, 2021
email us: firstname.lastname@example.org.