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While synthesis summarizes what the literature says, analysis assesses the strength of the evidence for drawing conclusions based on the synthesis.

**Analytical Methods for Quantitative Studies**

- Meta analysis
- Use of validity assessment
- Checking with authors of primary studies
- Subgroup analysis
- Sensitivity analysis
- Fixed effects analysis
- Random effects analysis
- Identifying gaps
- Risk of bias of individual studies
- Reporting bias because of dissemination issues

**Synthesis Approaches for Qualitative Studies**

- Grounded theory - constant comparison
- Meta-ethnography
- Meta-synthesis
- Meta-study
- Logical analysis
- Data analysis techniques
- Metaphorical analysis
- Domain analysis
- Hermeneutical analysis
- Analytic induction

Adapted from Booth, A. (2016). *Systematic approaches to a successful literature review* (Second edition.). Sage.

Meta analysis is a statistical technique that can be used to aggregate the results of individual quantitative studies.

- Deciding whether to base the analysis on a fixed- or random-effects model
- Fixed effect if the factor is assumed constant across studies and variation among studies is random

- Computing a summary estimate of effect (if appropriate)
- Weighted based on precision of estimates
- Inverse variance weighting (sample size/measurement error)

- Presenting the data (usually graphically)
- Usually a “forest plot” – point estimate and confidence interval of effect in each study

- Evaluating possible reasons for heterogeneity of study results (i.e. why different studies produce different estimates)
- Cochran’s Q, Higgins I2
- Subgroup analysis, stratified analysis
- graphical (Galbraith plot, scatterplot of effect size vs factor)
- meta regression (I2, adjusted R2, Tau2)

- Searching for evidence of publication bias and evaluating the influence that individual studies have on the outcome
- Funnel plot of each study’s SE against estimated effect
- Tests based on funnel plot (Begg, Egger)

- Last Updated: Aug 19, 2021 4:03 PM
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