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Effect sizes for experimental research
1Department of Statistics and Data Science, Northwestern University, Evanston, Illinois, USA.
Summary
Reporting effect sizes with statistical uncertainty is crucial for robust experimental research. This review covers various effect sizes and their standard errors for single and multiple degree-of-freedom treatments.
Area of Science:
- Statistics
- Experimental Design
- Quantitative Research Methods
Background:
- Scientific reporting standards necessitate effect size estimates alongside significance tests.
- Statistical best practices require quantifying the uncertainty of effect size estimates, often using standard errors.
Purpose of the Study:
- To review effect sizes commonly used in experimental research.
- To provide formulas for the standard error of various effect sizes.
- To cover effect sizes for treatments with single and multiple degrees of freedom.
Main Methods:
- Literature review of effect size measures in experimental statistics.
- Derivation and presentation of standard error formulas for selected effect sizes.
- Focus on effect sizes applicable to both simple (single degree of freedom) and complex (multiple degrees of freedom) treatment structures.
Main Results:
- Comprehensive overview of key effect size metrics.
- Formulas for calculating standard errors for each effect size are presented.
- Discussion includes effect sizes for fixed and random effects in multifactorial designs.
Conclusions:
- Accurate reporting of effect sizes and their uncertainty enhances the interpretability and reproducibility of experimental findings.
- The presented formulas facilitate the correct statistical analysis and reporting of experimental results.
- This work serves as a valuable resource for researchers seeking to implement best practices in statistical reporting.
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