Meta-Analysis in RevMan (Review Manager): A Practical Guide with Case Studies on Continuous and Dichotomous Data
Part A: Meta Analysis for Continuous Data:
Case Study 1:
Research Question
Does physical activity improve self-esteem in adolescents compared to no intervention?
Data:
| Study ID | Sample Size (Exercise Group) | Mean Self-Esteem (Exercise Group) | SD (Exercise Group) | Sample Size (Control Group) | Mean Self-Esteem (Control Group) | SD (Control Group) |
| Study 1 | 60 | 31.2 | 5.5 | 60 | 27.8 | 5.6 |
| Study 2 | 75 | 32.5 | 6 | 75 | 29 | 6.2 |
| Study 3 | 50 | 30.4 | 5.2 | 50 | 27.5 | 5.5 |
| Study 4 | 80 | 33 | 5.8 | 80 | 29.5 | 6 |
| Study 5 | 65 | 31.8 | 5.6 | 65 | 28.6 | 5.7 |
| Study 6 | 90 | 34 | 6.1 | 90 | 30 | 6.4 |
| Study 7 | 55 | 30.5 | 5.9 | 55 | 27.2 | 6 |
| Study 8 | 100 | 33.8 | 6.3 | 100 | 29.9 | 6.6 |
| Study 9 | 70 | 32 | 5.7 | 70 | 28.5 | 5.9 |
| Study 10 | 85 | 33.1 | 6.2 | 85 | 29.6 | 6.5 |
Data Description:
The dataset includes summary statistics from 10 studies comparing self-esteem scores between exercise and control groups, each providing sample size, mean, and standard deviation.
Step by Step Meta Analysis for Continuous data in RevMan:
Step 1: Add Included Studies, Select Studies and References Section then Click on Add Study to enter each individual Study and Year.
All 10 Studies Included:
Step 3: Click on Data Analysis Tab then Add Comparison insert Outcome Name and choose Continuous Outcome.
Step 4: Select Model (Random Effect) and Effect Measure (Standardized Mean Difference).
Step 5: Enter Data For each study, enter: Mean, Standard Deviation (SD) and Total Sample Size in each group (for both Treatment and control).
Step 6: To Generate Forest Plot, Click on Figure tab then Add Figure and Click Forest Plot, then Click Next and Select outcome thenclick on Finish.
Forest Plot:
Interpretation:
All studies report positive SMDs (0.54 to 0.64), showing a consistent moderate effect of physical activity on self-esteem. None of the confidence intervals cross zero, indicating each study found a statistically significant result. The overall pooled effect is 0.58 [95% CI: 0.48, 0.69], confirming a moderate and meaningful improvement in self-esteem. Heterogeneity is absent (τ² = 0.00, I² = 0%, Chi² = 0.3, p = 1.00), suggesting highly consistent findings across studies. The overall effect is statistically significant (z = 10.98, p < 0.00001), providing strong evidence for the positive impact of physical activity on adolescent self-esteem.
Step 7: To Generate Funnel Plot, Click on Figure tab then Add Figure and Click Funnel Plot, then Click Next and Select outcome thenclick on Finish.
Funnel Plot:
Interpretation:
The studies are symmetrically scattered around the pooled SMD (0.58), indicating no visual evidence of publication bias.
Part B: Meta Analysis for Dichotomous Data:
Case Study 2:
Research Question:
Does Drug A reduce the risk of infection compared to Placebo?
Data
| Study ID | Drug A Events | Drug A No Events | Drug A Total | Placebo Events | Placebo No Events | Placebo Total |
| Study 1 | 12 | 90 | 102 | 25 | 79 | 104 |
| Study 2 | 18 | 84 | 102 | 30 | 73 | 103 |
| Study 3 | 10 | 90 | 100 | 20 | 80 | 100 |
| Study 4 | 8 | 94 | 102 | 16 | 86 | 102 |
| Study 5 | 20 | 82 | 102 | 35 | 70 | 105 |
| Study 6 | 15 | 85 | 100 | 28 | 78 | 106 |
| Study 7 | 17 | 85 | 102 | 33 | 68 | 101 |
| Study 8 | 13 | 89 | 102 | 27 | 80 | 107 |
| Study 9 | 19 | 70 | 89 | 31 | 70 | 101 |
| Study 10 | 14 | 86 | 100 | 26 | 80 | 106 |
Data Description:
The dataset includes results from 10 studies comparing infection rates between patients receiving Drug A and those receiving a placebo. Each study reports the number of infection events and non-events in both groups as well as Total enabling the calculation of risk Differences.
Step by Step Meta Analysis for Dichotomous data in RevMan:
Step 1: Add Included Studies, Select Studies and References Section then Click on Add Study to enter each individual Study and Year.
All 10 Studies Included:
Step 3: Click on Data Analysis Tab then Add Comparison insert Outcome Name and choose Continuous Outcome.
Step 4: Select Model (Random Effect) and Effect Measure (Risk Difference).
Step 5: Enter Data For each study, enter: Event and Total for Treatment and Control Group.
Step 6: To Generate Forest Plot, Click on Figure tab then Add Figure and Click Forest Plot, then Click Next and Select outcome thenclick on Finish.
Forest Plot:
Interpretation:
The meta-analysis shows a pooled risk difference of -0.11 [95% CI: -0.15, -0.08], indicating Drug A reduces risk by 11% compared to placebo. All individual studies have negative risk differences, favouring Drug A, with several confidence intervals not crossing zero. Heterogeneity is very low (I² = 0%), suggesting consistent results across studies. The overall effect is statistically significant (p < 0.00001). The forest plot confirms the consistent beneficial effect of Drug A across all 10 studies.
Step 7: To Generate Funnel Plot, Click on Figure tab then Add Figure and Click Funnel Plot, then Click Next and Select outcome thenclick on Finish.
Funnel Plot:
Interpretation:
The studies are symmetrically scattered around the pooled Risk Difference (-0.11), indicating no visual evidence of publication bias.