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: How does sample size affect confidence intervals?
The sample size in a study significantly affects the width of the confidence interval:
- Higher sample sizes produce shorter CIs, increasing accuracy.
- low sample sizes yield in broader CIs, indicating higher uncertainty.
In the continuous outcomes, variation in the data also impacts precision, but in the dichotomous outcomes, it is based on event risk.
In meta-analysis, confidence intervals tend to shorten as large studies are included, while if variability increases, CIs may widen.
Reference:
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