Meta Analysis 2
This course will teach you advanced issues in meta-analysis and the statistical analyses that are used to synthesize summary data from a series of studies.
Overview
Meta-Analysis refers to statistical analyses used to synthesize summary data from a series of studies. This course continues the course of study begun with Meta Analysis 1. Participants will briefly review material covered in Meta Analysis 1, then cover meta-regression, power analysis, interpretation of results in terms of effect-sizes and the relationship with p-values, and considerations in psychometric meta-analysis. They will also study publication bias, vote-counting, and criticisms of meta-analysis.
- Intermediate
- 4 Weeks
- Expert Instructor
- Tuiton-Back Guarantee
- 100% Online
- TA Support
Learning Outcomes
Students who complete this course will be able to formulate a research question relevant to their area of interest in a format that is appropriate for meta-analysis. They will learn how to perform a basic literature search and how to evaluate studies for inclusion in their analysis. They will develop the ability apply the appropriate statistics to a dataset supplied by the instructor, and to interpret the results .They will be able to demonstrate that they can apply the skills taught in this course as well as the skills they learned in Meta-Analysis 1.
- Use fixed and random effects models appropriately
- Conduct subgroup analyses
- Work with multiple outcomes within studies
- Describe and assess publication bias
- Conduct sensitivity analysis
Who Should Take This Course
Researchers who plan to perform a meta-analysis, or who want to be able understand meta-analyses that have been published by others.
Our Instructors
Dr. Michael Borenstein
Course Syllabus
Week 1
- Review of basic issues in meta-analysis
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- Effect Sizes
- Fixed and Random Effects
- Heterogeneity
- Prediction Intervals
Week 2
- Meta-Analysis in the Context of a Systematic Review
- Formulating a Research Question
- Searching the Literature
- Developing Inclusion and Exclusion Criteria
Week 3
- Assessing Study Quality
- Creating a Coding Sheet
- Calculating Effect Sizes
Week 4
- Analyzing a dataset
- Testing for Publication Bias
- Interpretation of analyses
Class Dates
2023
Instructors: Dr. Michael Borenstein
2024
Instructors: Dr. Michael Borenstein
2025
Instructors: Dr. Michael Borenstein
Prerequisites
Meta Analysis 1
- Skill: Intermediate
- Credit Options: CEU
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Additional Information
Homework
Homework in this course consists of short answer questions to test concepts and guided data analysis problems using software.
In addition to assigned readings, this course also has an end of course data modeling project, short narrated software demos, and supplemental readings available online.
Course Text
There are two required course texts: the first is Introduction to Meta-Analysis, by Borenstein, Hedges and Higgins, the second is Research Synthesis and Meta-Analysis: A Step by Step Approach, 5th edition, by Cooper.
Be sure to order these texts prior to the course start date.
Software
The course includes illustrations and exercises using Microsoft Excel. Participants will also be given access to the software Comprehensive Meta-Analysis during the first week of the course, and will learn how to use this program to conduct advanced analyses.
Please be aware that this software program is for Windows only, and will not run on Mac OS platforms.
Supplemental Information
Literacy, Accessibility, and Dyslexia
At Statistics.com, we aim to provide a learning environment suitable for everyone. To help you get the most out of your learning experience, we have researched and tested several assistance tools. For students with dyslexia, colorblindness, or reading difficulties, we recommend the following web browser add-ons and extensions:
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Firefox
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