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 the interpretation of P values?

P values depend on both the effect estimate and the sample size (or the precision of the effect estimate).

Larger sample sizes reduce the range of effects that could occur by chance, leading to smaller P values for the same effect size.
This means that a larger study is more likely to produce a statistically significant result, even if the effect is clinically trivial.

References:

Cochrane Handbook for Systematic Reviews of Interventions. (2011). 4.2 P values and statistical significance. The Cochrane Collaboration. Retrieved from
https://handbook-5-1.cochrane.org/chapter_12/12_4_2_p_values_and_statistical_significance.htm

Q: How does sample size affect the interpretation of P values?

References:

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