Meta-Analysis Basic Course
Meta-Analysis easy to do
Online Education,Teaching & Academics,Data Analysis
Lectures -7
Duration -46 mins
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Course Description
Meta-analysis is an important statistical approach to validly combine the results of studies following a systematic review. This course takes you through the concepts of meta-analysis and the various graphical representation required to display the results. A complete understanding of concepts is required to properly interpret the results to the scientific world. The two important types of data, binary and continuous, and their pooled estimates are discussed in simple language with relevant examples for you to understand better. This will form the basis for your understanding to perform the meta-analysis. The RevMan software offered free by the Cochrane Collaboration is a sturdy application to do meta-analysis, with the image quality good for journal publication. The figures generated are standard and comparable to other images from other applications. I personally will recommend this application for beginners in meta-analysis.
Heterogeneity is variations among the studies which are included in the meta-analysis. Understanding the various types of heterogeneity and how it impacts the interpretation of the results from meta-analysis is important. The course also deals with the learning and generation of forest and funnel plots. They are the graphical presentation of data and results displayed in the form of a scatter plot. These plots give a bird’s eye view of the results, their meaning, and interpretation.
Come join this course and take yourself to the next level in understanding and interpreting meta-analysis and become a part of cutting-edge research.
Goals
Be able to perform meta-analysis
Be able to use the RevMan Software to do meta-analysis
Be able to explain the various types of heterogeneity
Be able to generate and interpret forest and funnel plots
Prerequisites
Be able to understand simple instructions and to search for information online
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
1 Lectures
- Introduction 05:34 05:34
Data Analysis and Estimates
3 Lectures
Heterogeneity and Plots
3 Lectures
Instructor Details
shaju Jacob
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