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 is the correlation between P values and confidence intervals?

There is a strong relationship between confidence intervals P values and confidence intervals

If the CI support the null value, the P value is ≥ 0.05, reflects not sufficient evidence for observed effect.
If the 95% CI rejects the null value (e.g., an odds ratio of 1.0), the corresponding P value is < 0.05, indicates statistical significance is confirmed.

For instance:

CI: 0.70 (95% CI: 0.60 to 0.80) → Statistically Significant effect (P < 0.05)
CI: 1.05 (95% CI: 0.90 to 1.20) → Not statistically significant (P ≥ 0.05)

Reference:

Cochrane Handbook for Systematic Reviews of Interventions. (2011). 4.1 Confidence intervals. The Cochrane Collaboration. Retrieved from

https://handbook-5-1.cochrane.org/chapter_12/12_4_1_confidence_intervals.htm

Q: What is the correlation between P values and confidence intervals?

Reference:

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