Data analysis
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The data analysis part of evidence synthesis is where the extracted data from individual studies are combined, interpreted, and presented to answer the review question.
The approach to data analysis depends heavily on the type of data collected (quantitative, qualitative, or mixed) and the specific aims of the evidence synthesis.
The analysis aims to identify patterns, consistencies, or discrepancies in the evidence.
Understands that there are a range of evidence synthesis methods for analysing different types of data.
Contributes to basic data analysis, for example selecting elements of extracted data to be tabulated for inclusion in the report.
Creates graphs such as bar charts, or choropleths to display results under direction.
Creates a variety of tables and graphs to present results using own initiative.
Analyses, tabulates and writes up characteristics of included studies to understand the studies in the review.
Cleans and transforms data ready for analysis.
In quantitative synthesis, interprets a broad range of statistical analyses/measures of effect (e.g. odds ratios, standard mean difference, confidence intervals, heterogeneity).
Conducts synthesis of extracted data (e.g. meta-analysis, meta-regression, qualitative synthesis, narrative synthesis). Understands and interprets results from data analysis.
Designs and/or delivers training on data analysis/synthesis.
Evaluates and promotes data evidence synthesis methods across your organization.
Leads and promotes the development of data analysis methods on a national and international basis.