Analysing and interpreting data

Types of analysis 
Narrative analysis techniques
Meta-analysis
Software for meta-analysis

Types of analysis 

How you analyse your evidence will depend on the scope of your review question, the types of studies included, and the nature of the data extracted.  

  • Narrative analysis: a structured summary, comparing the data, and identifying themes to demonstrate evidence of an effect. 
  • Meta-analysis: pooling and analysing the results across several studies using statistical methods. 
  • Integrative analysis: synthesising diverse datasets using both narrative and statistical analysis. Use this for studies of varied study designs or mixed-methods approaches.

Narrative analysis techniques

Technique

Advantages

Limitations

Text description: consistently annotate individual studies with an organised summary of characteristics 

Keeps details of each study together 

Difficult to see themes 

Tabulation: create a table of study elements and findings 

Compares characteristics 

Does not synthesise 

Categorise: group or cluster studies around particular characteristic(s) 

Visualise patterns 

Difficult to see relationships across categories 

Thematic analysis: analyse content with a rubric to identify themes and factors 

Consistency 

Time needed to develop a rubric 

Describe relationships: identify relationships between primary study findings and characteristics to determine differences within and between studies.  

Provides sub-analysis 

Difficult with a large number of studies 

(Booth, Papaioannau & Sutton, 2012)

Meta-analysis

A meta-analysis involves pooling and analysing the results across multiple studies using statistical methods. 

You might conduct a meta-analysis as part of your systematic review to:

  • increase the chance of detecting a statistically significant outcome or effect
  • improve precision
  • answer questions not posed by the individual studies
  • settle controversies arising from apparently conflicting studies
  • generate new hypotheses.

(Cochrane Handbook, Section 10.2 'Introduction to meta-analysis')

A meta-analysis should only be performed if you have a group of studies that are similar. The studies should be homogeneous in terms of participants, interventions and outcomes, so that the meta-analysis can draw a meaningful conclusion.

A meta-analysis can be performed on observational studies, studies with multiple outcomes, and studies with diverse methodological approaches. The Sydney Informatics Hub can help researchers figure out whether performing a meta-analysis using the studies they have extracted data from is possible.

Software for meta-analysis

  • NVivo Qualitative data analysis software that can handle rich text-based information. It automates many manual tasks associated with analysis, like data classification and sorting.
  • SPSS Software used for statistical meta-analysis. Available on campus desktop computers through the Citrix Workspace app.
  • SAS Statistical software that allows you to perform data management, visualisation and prediction. You will need to accept the SAS Student Use Agreement online to obtain a copy of SAS.
  • 'Practical Meta-analysis Effect Side Calculator' Calculates effect sizes for meta-analyses. This too can calculate the standardised mean difference, correlation coefficient, the odds-ration, and the risk ratio.

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