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How to Conduct a Meta-analysis: A Practical Guide
Rating: 4.1 out of 5(182 ratings)
3,320 students

How to Conduct a Meta-analysis: A Practical Guide

#1 Meta-Analysis Course for Researchers: A Practical Approach to Synthesizing Data
Last updated 2/2024
English

What you'll learn

  • Introduction to Meta-Analysis
  • Data Extraction and Effect Size Calculation
  • Fixed-Effect and Random-Effects Models
  • Heterogeneity Assessment and Moderator Analysis
  • Reporting and Interpretation of Results
  • Open Science Practices and Data Sharing
  • Choosing appropriate effect sizes and measures for meta-analysis
  • Understanding the concept of publication bias and how to assess it
  • Using software tools for conducting and visualizing meta-analyses, such as SPSS, SAS, R and Comprehensive Meta-Analysis

Course content

10 sections34 lectures2h 24m total length
  • Instructor Introduction2:15
  • What is Meta-analysis?4:43
  • What is the importance of meta-analysis in Academia?4:14
  • Disadvantages of meta-analysis1:55
  • Steps in meta-analysis2:37

Requirements

  • Basic knowledge of statistics
  • Familiarity with research methodology
  • Knowledge of statistical software
  • Good analytical skills
  • Motivation and commitment

Description

Meta-analysis is a powerful statistical technique that allows researchers to synthesize and integrate findings from multiple studies, providing a more comprehensive and accurate understanding of a research topic. Whether you're a graduate student, academic researcher, or industry professional, this course will provide you with a thorough understanding of the principles and practical skills needed to conduct and interpret meta-analyses.


Master the Principles and Practical Skills of Conducting Meta-Analyses


  • Understand the purpose, benefits, and limitations of meta-analysis

  • Learn how to conduct a systematic literature review and identify relevant studies for inclusion

  • Extract data from primary studies and calculate effect sizes with confidence

  • Perform meta-analyses using both fixed-effect and random-effects models

  • Assess heterogeneity and conduct moderator analyses to explore sources of variation

  • Report meta-analytic results and interpret their practical and theoretical implications

  • Incorporate open science practices and utilize online resources for collaboration and data sharing

What You’ll Learn in This Course

In this course, you'll gain a deep understanding of the core principles of meta-analysis, starting with its purpose, benefits, and limitations. You'll learn how to conduct a systematic literature review to identify relevant studies and extract data for analysis. We’ll cover the key techniques for performing meta-analyses using both fixed-effect and random-effects models, as well as how to assess heterogeneity and explore sources of variation through moderator analyses.

You'll also learn how to report meta-analytic results and interpret their implications for both practical and theoretical contexts. With a focus on open science practices, you'll understand how to utilize online resources for collaboration and data sharing in meta-analysis.

By the end of the course, you will have the knowledge and skills necessary to confidently conduct your own meta-analyses, evaluate existing meta-analyses, and contribute to advancing your field of study. Whether you’re conducting meta-analyses or interpreting the results, this course will prepare you to navigate the world of meta-analysis with confidence.

Who this course is for:

  • Graduate students
  • Academicians
  • Researchers
  • Industry professionals