Meta-analysis is a set of techniques used “to combine the results of a number of different reports into one report to create a single, more precise estimate of an effect” (Ferrer, 1998). The aims of the meta-analysis are “to increase statistical power; to deal with controversy when individual studies disagree; to improve estimates of the size of the effect, and to answer new questions not previously posed in component studies” (Hunter and Schmidt, 1990).
A meta-analysis would be used for the following purposes:To establish statistical significance with studies that have conflicting results
To develop a more correct estimate of effect magnitude
To provide a more complex analysis of harms, safety data, and benefits
To examine subgroups with individual numbers that are not statistically significant
Steps in a meta-analysis
A meta-analysis is usually preceded by a systematic review, as this allows identification and critical appraisal of all the relevant evidence (thereby limiting the risk of bias in summary estimates). The general steps are then as follows;
- Formulation of the research question, e.g. using the PICO model (Population, Intervention, Comparison, Outcome).
- Search of literature
- Selection of studies ('incorporation criteria')
- Based on quality criteria, e.g. the requirement of randomization and blinding in a clinical trial
- Selection of specific studies on a well-specified subject, e.g. the treatment of breast cancer.
- Decide whether unpublished studies are included to avoid publication bias
4. Decide which dependent variables or summary measures are allowed. For instance, when considering a meta-analysis of published (aggregate) data:
5. Selection of a meta-analysis model e.g. fixed-effect or random-effects meta-analysis.
6. Examine sources of between-study heterogeneity, e.g. using subgroup analysis