This course provides an introduction to 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 a step-by-step guide for meta-analyses, from developing a research question suited for a meta-analysis to analyze and interpret the data. The course also aims at developing a methodological understanding of both the strengths and weaknesses of meta-analyses.
KCE collaborates nationally and internationally, and we will involve our partners in delivering PhD courses, ensuring that PhD students have access to a wide range of prominent researchers in the field.
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. Stages of a systematic review that includes a meta-analysis
The course will provide an overview of the stages of a systematic review from problem formulation through literature searching, screening, data extraction, meta-analysis and interpretation. At each stage, you will get practice at conducting the methods using freely available tools.
3. Meta-analysis methods
The course will provide an introduction to the three main effect sizes used in meta-analysis: standardized mean differences, correlations and odds ratios. You will also be introduced to basic meta-analysis methods, including estimating the mean effect size and exploring effect size heterogeneity. Graphical techniques for presenting effect sizes and exploring publication bias will also be discussed.
4. Critically appraising research articles in a meta-analysis
Following the introduction to systematic review and meta-anlaysis, we will carefully examine research articles in a meta-analysis and discuss their quality using different appraisal tools and knowledge gained in the course.
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
By completion of this course, the PhD candidate will have gained following skills:
- Framing a relevant research question suited for meta-analyses
- Building a high-quality search strategy
- Screening for eligible studies
- Data extraction including assessing the quality of research articles in a meta-analysis
- Methods for meta-analysis including computing effect sizes and exploring effect size distributions
- 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.
Form of assessment
Passed / Not Passed
Coursework requirements: at least 80% attendance.Exam: Course Assessment: Pass / fail based on the following: Weight Duration Marks Aid Portfolio evaluation Active participation and completion of small assignments during the course, as well as a final paper (min 2000-3000 words), which includes evaluating an existing meta-analysis. The portfolio is assessed (pass/fail) and participants will receive constructive feedback on their paper.
Lectures, small individual and group assignments during the course, and submission of an individual final paper.
Students enrolled in a PhD program. If any available space, the admission will also be open to researchers and master students. Applicants may be turned down due limitations in number of places (max. 20 participants).
There must be an early dialogue between the course coordinator, the student representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital course evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.