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Should Pearson's correlation coefficient be avoided?
1School of Life and Health Sciences: Ophthalmic Research Group, School of Optometry, Aston University, Birmingham, UK.
Summary
This study surveyed statistical methods in ophthalmic literature, finding limited adherence to Pearson
Area of Science:
- Ophthalmic research
- Statistical analysis
- Biometry
Background:
- Pearson's correlation coefficient (r) is frequently used in ophthalmic literature.
- Understanding the limitations and appropriate application of statistical methods is crucial for valid research.
- The use of correlation coefficients requires careful consideration of data distribution and assumptions.
Purpose of the Study:
- To assess the application of Pearson's correlation coefficient (r) in ophthalmic journals.
- To identify limitations associated with the use of Pearson's r.
- To recommend alternative statistical methods when appropriate.
Main Methods:
- Systematic search of online archives for Ophthalmic and Physiological Optics, Optometry and Vision Science, and Clinical and Experimental Optometry.
- Keywords used included 'correlation' and 'Pearson's r'.
- Analysis of the frequency of use for various correlation coefficients and related statistical concepts.
Main Results:
- Pearson's r was frequently used, but assumptions like bivariate normality were rarely addressed.
- Spearman's rank correlation and intra-class correlation coefficient (ICC) were also employed.
- Limited attention was given to sample size issues and the interpretation of correlation as causality.
Conclusions:
- Investigators should critically evaluate the assumptions and limitations of Pearson's r.
- Consideration of non-linearity, data distribution, outliers, sample size, and causality is essential.
- A more cautious approach to using Pearson's r and exploring alternative methods is recommended.
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