Meta-Analysis – June 2023

Event Phone: 610-715-0115

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In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.

A 4-Day Remote Seminar
Taught by David Wilson, Ph.D.

How do you make sense of conflicting results across studies? It is common for a finding that is statistically significant in one study to be statistically nonsignificant in another. Does this reflect differences in the design of the studies? Do the effects actually agree in direction and magnitude even if they are different in statistical significance? What if we have 5 such studies, or 50, or 500? It would be surprising if all such studies were in perfect agreement with one another. Thus, we need a method to make sense of the variability in findings across studies.

Meta-analysis is a statistical solution to this problem and has become a widely-used method for synthesizing results across studies in the social, biomedical and physical sciences. The key to meta-analysis is the effect size: it encodes the direction and magnitude of the finding on a common scale. Using specialized statistical methods, the average effect across studies can be estimated as well as an examination of the consistency of the effects. Analyses can also explore potential explanations for inconsistencies in findings, such as theoretically relevant design differences.

This course will provide hands-on instruction in conducting all aspects of a meta-analysis. You’ll learn to systematically search for studies to include in a meta-analysis, to code and extract data systematically, to compute effect sizes of various types, and to estimate both fixed and random-effects meta-analysis models. Finally, you will learn how to report and present the results of a meta-analysis.

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