Meta-research: Appraising Research Findings, Bias, and Meta-analysis
The course comprises two complementary tracks that run in parallel and reinforce each other. The first track addresses meta-research and the empirical study of science and research practices in large-scale. The second track of the course covers the main methods of evidence synthesis, systematic reviews and meta-analysis, with the aim of making students capable of performing competent systematic reviews and meta-analyses. The course includes the generation of a meta-research project or reworking and evaluating an existing published meta-analysis.
NOTE: This course updated its course number, please enroll under the new course number EPI206.
What you will learn
- How to appraise the quality and credibility of research findings
- How to evaluate sources of bias
- How to use meta-analysis as a quantitative (statistical) method
Prerequisites: A minimum knowledge of basic statistics and familiarity with R is strongly recommended (alternatively students should be able to use some other software for meta-analysis).
- Inference methods in scientific investigation
- Principles of evidence
- Statistical significance and other types of significance
- Assessment of the credibility of evidence
- Optimal study designs for obtaining reliable evidence
- Optimal design, reporting, conduct, review of scientific investigations
Systematic reviews and meta-analysis
- An overview of evidence synthesis
- Systematic literature review methods
- The basics of meta-analysis methods
- Advanced meta-analysis topics
This class is credit/no credit. For it to count towards the certificate, you must earn credit.
The course schedule is displayed for planning purposes – courses can be modified, changed, or cancelled. Course availability will be considered finalized on the first day of open enrollment. For quarterly enrollment dates, please refer to our graduate certificate homepage.
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