meta-analysis
Sign in to saveMeta-analysis is a method of synthesis of quantitative data from multiple independent studies addressing a common research question. An important part of this method involves computing a combined effect size across all of the studies. As such, this statistical approach involves extracting effect sizes and variance measures from various studies. By combining these effect sizes the statistical power is improved and can resolve uncertainties or discrepancies found in individual studies. Meta-analyses are integral in supporting research grant proposals, shaping treatment guidelines, and influencin
Article
27 sectionsContents
- History
- Literature search
- Methods and assumptions
- Approaches
- Statistical models for aggregate data
- Fixed effect model
- Random effects model
- Quality effects model
- Network meta-analysis methods
- Bayesian framework
- Frequentist multivariate framework
- Generalized pairwise modelling framework
- Diagnostic test accuracy meta-analysis
- Aggregating IPD and AD
- Validation of meta-analysis results
- Challenges
- Publication bias: the file drawer problem
- Problems related to studies not reporting non-statistically significant effects
- Problems related to the statistical approach
- Problems arising from agenda-driven bias
- Comparability and validity of included studies
- Weak inclusion standards lead to misleading conclusions
- Applications in modern science
- Software
- See also
- Sources
- References
Meta-analysis is a method of synthesis of quantitative data from multiple independent studies addressing a common research question. An important part of this method involves computing a combined effect size across all of the studies. As such, this statistical approach involves extracting effect sizes and variance measures from various studies. By combining these effect sizes the statistical power is improved and can resolve uncertainties or discrepancies found in individual studies. Meta-analyses are integral in supporting research grant proposals, shaping treatment guidelines, and influencing health policies. They are also pivotal in summarizing existing research to guide future studies, thereby cementing their role as a fundamental methodology in metascience. Meta-analyses are often, but not always, important components of a systematic review.
==History==