Course
Advanced Meta-Analysis (DUH200)
Facts
Course code DUH200
Credits (ECTS) 5
Semester tution start Spring
Language of instruction English
Number of semesters 1
Exam semester Spring
Time table View course schedule
Literature Search for literature in Leganto
Introduction
This course discusses advanced methods for systematic reviews with a meta-analysis. There are many different types of systematic reviews, but they all have in common that they are a synthesis of existing knowledge, and they utilize transparent and explicitly defined procedures to find, evaluate and synthesize the results of relevant research with minimum bias. In this course, systematic review with a meta-analysis, which is used to analyze and synthesize quantitative research, will be covered.
This course will provide advanced methods for meta-analyses, from developing a research question suited for a meta-analysis to analyzing and interpreting the data using models that better reflect the structure of meta-analysis data. The course also aims at developing a methodological understanding of both the strengths and weaknesses of meta-analyses.
Content
1. What are systematic reviews with a meta-analysis?
Here, you will become acquainted with what a meta-analysis is, the value of meta-analyses, as well as its strengths and weaknesses.
2. Meta-analysis methods
The course will review the three main effect sizes used in meta-analysis: standardized mean differences, correlations and odds ratios. The course will also discuss effect sizes relevant for more complex analyses included in primary studies such as those for clustered randomized trials or adjusted for covariates. You will also be introduced to principles for meta-analysis models, including estimating the mean effect size and exploring effect size heterogeneity using multilevel and correlated models. Graphical techniques for presenting effect sizes and exploring publication bias will also be discussed.
3. Critically appraising research articles in a meta-analysis
Following the introduction to systematic review and meta-analysis, we will carefully examine research articles in a meta-analysis and discuss their quality using different appraisal tools and knowledge gained in the course.
Learning outcome
Knowledge
By completion of this course, the PhD candidate will have knowledge about:
- What a meta-analysis is and main principles of evidence synthesis methods
- The phases in conducting a meta-analysis/ Planning a meta-analysis
- Statistical analysis including various effect sizes, heterogeneity, moderator analysis, publication bias
- Interpreting the results/evidence
Skills
By completion of this course, the PhD candidate will have gained following skills:
- Framing a relevant research question suited for meta-analyses
- Methods for meta-analysis including computing a range of effect sizes and exploring effect size distributions
- Estimating and interpreting multilevel and correlated effect size models for meta-analysis
General competences
- Critical research literacy
- Statistical analysis knowledge
Required prerequisite knowledge
Students must be enrolled in a PhD program. PhD candidates at other universities and university colleges in Norway and EEA can apply for admission to the course. The students should also be familiar with basic statistical knowledge.
External candidates must use the application form for enrollment to the class, and send it to phd-uh@uis.no
Exam
Portfolio evaluation
Weight 1/1
Marks Passed / Not Passed
Active participation and completion of small individual and group assignments during the course, as well as a final paper (min 3000 words), which include writing up a protocol OR evaluating existing meta-analyses. The portfolio is assessed (pass/fail) and participants will receive constructive feedback on their paper.