What is effect size in meta-analysis?
An example of an AI chatbot conversation about effect size in meta-analysis.
What is effect size in meta-analysis?
Effect size is a quantitative measure of the magnitude of a phenomenon. In meta-analysis, it helps summarize the strength of the results across studies.
Why is effect size important in research?
Effect size provides context to the statistical significance, allowing researchers to understand the practical implications of their findings.
Can you give me examples of effect size measures?
Sure! Common measures include Cohen's d, Pearson's r, and odds ratios, each serving different types of data and research designs.
How do I calculate effect size?
The calculation depends on the type of data. For example, Cohen's d is calculated by taking the difference between two group means and dividing by the pooled standard deviation.
What are the limitations of effect size?
Limitations include potential misinterpretation, dependence on sample size, and the fact that it doesn't convey the direction of the effect.
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