Mean and Mean difference are the two key statistical measures used in the statistical analysis. Both are essential for meta-analysis as well. Mean and Mean difference are used for the interpretation of a large set of values into a single number which explains the heterogeneity and variation among the individual values. However, one of a common challenge in meta-analysis is the unavailability of this data (mean and standard deviation).
Q & A Forum
Meta Analysis
Q: What are confidence intervals, why they are important in meta-analysis?
Confidence intervals (CIs) refer the range within which the intervention effect is likely lies, indicating a magnitude of uncertainty around point estimate. They are reported along with point estimates including odds ratios.
For instance, assume that a study implying, “The odds ratio was 0.70 with a 95% CI of 0.65 to 0.75”, the estimate (0.70) indicates the best estimate of the intervention’s observed effect, but the confidence interval (0.65 to 0.75) represents the range of values within which the true effect likely to be exists.
A short confidence interval states a low uncertainty and precise estimate, while a broader interval depicts higher uncertainty, insisting more data may be required.
References:
- Cochrane Handbook for Systematic Reviews of Interventions. (2011). 12.4.1 Confidence intervals. The Cochrane Collaboration. Retrieved from
- https://handbook-5-1.cochrane.org/chapter_12/12_4_1_confidence_intervals.htm