Analysing and interpreting data

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




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 


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)


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. 

Types of systematic review that are not appropriate for meta-analysis include those based on:  

  • non-randomised studies 
  • studies with multiple outcomes 
  • studies with diverse methodological approaches.

In these instances, a systematic review can only be conducted using narrative analysis techniques.   

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.
  • Contact

    For help with planning and performing searches, speak with library staff.

    Contact a librarian