Pre-define analyses
This page details the steps to create analyses using study data.
From 3 June 2024, all intervention and flexible (rapid) reviews and protocols of these review types have study-centric data management enabled as a default system setting. See study-centric data management.
Study-centric data management does not prevent you from setting up and editing manual-input analyses in your review. See Set up a manual-input analysis.
Types of analyses in RevMan
There are two ways to set up an analysis in RevMan:
- Using study data: All studies with results for the selected outcome and interventions will be included in the analysis. Data are entered and stored at the included study level and can be re-used across different analyses.
- Using manual input: Manually choose which studies are included in the analysis. Data are entered and stored specifically for this analysis and cannot be re-used across different analyses. See here for more details.
Add an Analysis using study data
After setting up the review criteria, it is recommended that authors set up their analyses at the protocol stage before entering any study results data. This enables you to check that you have included the Interventions, Intervention groupings, Outcomes and Covariates within the Review criteria correctly. It also means that once you import your results data, your analyses will be automatically populated (a key benefit of using study centric data management).
First, set up an Analysis group as described here (create an Analysis group, name the Analysis group and create an analysis).
Go back to the main Analyses page, expand the panel for the Analysis group that you just created by clicking on its name. Then click Add Analysis. You are prompted whether you would like to create an analysis based on study data or custom input. Choose Automatic.
Define the name of the new analysis and data source
On the new Analysis page, first enter a name (in this case it makes sense to just enter the outcome name) and select the data source. The data source relates to the types of results data to include in your analyses, with the options:
- Only arm-level data
- Only contrast-level data
- Contrast- and arm-level data (preferring arm-level data where both exist)
- Contrast- and arm-level data (preferring contrast-level data where both exist)
More information about arm level and contrast level data is available, and Section 5.3.6 of the Cochrane Handbook for Systematic Reviews of Interventions provides more guidance on the different types of data and in what circumstances either might be preferred in your analyses.
Set the Synthesis PICO
On the new Analysis page, under Synthesis PICO, choose your:
- Outcome
- Intervention grouping (for broader synthesis questions), experimental intervention (for narrower synthesis questions) and control intervention.
The example shows a broad synthesis question using intervention groupings. It includes 'Persistent symptoms after 7 days' as the Outcome, 'Antibiotics' (all antibiotics) as the Experimental Intervention and 'Placebo' as the Control Intervention. None of the following examples subgroup or filter for sensitivity analyses, so these options are left as default.
When using an intervention grouping like this to define a comparison, it is useful to name the grouping with a description of the comparison - "Any antibiotic vs any placebo" in this example
The example shows a narrower synthesis question using the more granular interventions based on a specific antibiotic versus placebo. It includes 'Persistent symptoms after 7 days' as the Outcome, 'Tetracycline' as the Experimental Intervention and 'Placebo' as the Control Intervention.
The example shows a narrower synthesis question using the more granular interventions based on antibiotic coverage. It includes 'Persistent symptoms after 7 days' as the Outcome, ' Broad-spectrum antibiotic' as the Experimental Intervention and 'Narrow spectrum antibiotics' as the Control Intervention.
How are study centric data analyses generated?
Study centric data analyses are generated by RevMan based on the criteria you set up in each analysis. Depending on the data source, outcome, interventions, subgroup or filter for sensitivity, and the available data, RevMan will identify which results to include. To optimize the amount of data to include, RevMan will automatically transform result data with the following operations:
- Combine study arms when two or more study arms map to the interventions selected for the analysis (available for both contrast and arm level data)
- Transform arm level data to contrast level data when including both arm and contrast level data in an analysis
- Switch reference arm when a study reports the contrasts A-B and A-C were reported and you are interested in the contrast B-C.
Note that a result will only be included if there is enough data available. When you are setting up subgroup or sensitivity analyses, you will need to have specified the covariates in advance.
View a complete explanation of how study centric analyses are generated.
To add footnotes to the forest plot of a study centric data analysis, see Add footnotes to study-centric results.