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GPDI548 - Meta-Analysis from A to Z

This workshop focuses on the practical “how to” of quantitative research synthesis. Preventive health research, like many disciplines, has a body of empirical research that is growing rapidly. Over the last four decades, data science aggregation and statistical methods have been developed to systematically and reproducibly synthesize the literature for a particular research question. These methods are commonly incorporated under the terms research synthesis or meta-analysis. Meta-analysis is used to derive an estimate of an overall effect size, combined with detailed moderator analyses with respect to the diversity and sensitivity of results.


Requirements:
Participants must have a working knowledge of R and will need to bring their own laptop with R (version 3.4 or above) and Rstudio installed. To learn how to install R and RStudio, please use the following resources:

Linux: https://youtu.be/YBOpy1WK-bg
Mac OS: https://youtu.be/GFImMj1lMRI
Windows: https://youtu.be/GAGUDL-4aVw
We will be also be using several R packages including metafor
Here is a quick guide on how to install an R package:
https://youtu.be/u1r5XTqrCTQ

Learning Objectives


In this workshop participants will learn how to:
1. Formulate a research question
2. Search and evaluate the literature
3. Extract and code data
4. Analyze and interpret meta-analytic models.

Leaders Information


This workshop is led by Jennifer J McGrath, PhD MPH, PERFORM Chair in Childhood Preventive Health & Data Science and founder of Data Scientifique, an initiative that fosters data science opportunities among researchers. She has pioneered rigorous pediatric ambulatory measurement standards and advocates for reproducibility of science through open-source data science methods. Dr. McGrath has facilitated several meta-analyses through to completion, spanning diverse topics such as heart rate variability, executive functioning, socioeconomic status, racial discrimination, and goal adjustment.

This workshop is not scheduled at this time.
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