Vitskaplege metodar: Meta-Analyse
Ph.d.-kurs
- Studiepoeng
- 2
- Undervisningssemester Haust, Vår
- Emnekode
- CDP924
- Talet på semester
- 1
- Ressursar
- Timeplan
Emnebeskrivelse
Læringsutbytte
On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:
The candidate should have knowledge about:
- what defines meta-analysis and its pros and cons
- variance and precision of effects sizes
- methods for coding of study quality
- effect size heterogeneity
- different biases in meta-analysis
- sensitivity analysis
- typical errors in meta-analysis and how to avoid them
Skills:
The candidate should be able to
- conduct systematic literature searches
- calculate effects sizes based on a wide range of effect types
- conduct fixed effects and random effects meta-analyses
- measure effect size heterogeneity
- correct for/control for biases
- perform moderator and meta-regression analyses
- accurately and systematically report meta-analytic data
General competence:
The candidate should:
- possess knowledge about meta-analytic procedures, be able to critical evaluate meta-analyses and to conduct meta-analyses and report meta-analytic data
Undervisningsperiode
Studiepoeng
Undervisningssted
Undervisningsspråk
Påmelding og -frister
Forkunnskapskrav
Anbefalte forkunnskaper
Vurderingsform
For this course several evaluation forms are been used:
- Presence
- Mandatory paper
Hvem kan delta
Utfyllende kursomtale
Objectives
The course provides a basic introduction to meta-analysis as a tool for research synthesis.
The aims are to give the candidates both a theoretical and practical introduction to meta-analysis; to equip the candidates with skill necessary to conduct meta-analyses and report results from meta-analyses.
Content
The course contains themes such as:
- systematic literature search
- extraction of data for meta-analysis
- running fixed and random effect size meta-analyses