This is an archived version of the Handbook. For the current version, please go to or search for this chapter here.  The generic inverse variance outcome type in RevMan

Estimates and their standard errors may be entered directly into RevMan under the ‘Generic inverse variance’ outcome. The software will undertake fixed-effect meta-analyses and random-effects (DerSimonian and Laird) meta-analyses, along with assessments of heterogeneity. For ratio measures of intervention effect, the data should be entered as natural logarithms (for example as a log odds ratio and the standard error of the log odds ratio). However, it is straightforward to instruct the software to display results on the original (e.g. odds ratio) scale. Rather than displaying summary data separately for the treatment groups, the forest plot will display the estimates and standard errors as they were entered beside the study identifiers. It is possible to supplement or replace this with a column providing the sample sizes in the two groups.


Note that the ability to enter estimates and standard errors directly into RevMan creates a high degree of flexibility in meta-analysis. For example, it facilitates the analysis of properly analysed cross-over trials, cluster-randomized trials and non-randomized studies, as well as outcome data that are ordinal, time-to-event or rates. However, in most situations for analyses of continuous and dichotomous outcome data it is preferable to enter more detailed data into RevMan (i.e. specifically as simple summaries of dichotomous or continuous data for each group). This avoids the need for the author to calculate effect estimates, and allows the use of methods targeted specifically at different types of data (see Sections 9.4.4 and 9.4.5). Also, it is helpful for the readers of the review to see the summary statistics for each intervention group in each study.