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Accounting for Eye Correlation Improves Statistical Accuracy

Study compares methods for analyzing data from both eyes

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    - The study focuses on statistical models in ophthalmic research. - Treating both eyes as independent leads to inflated false-positive rates. - Mixed effects models are preferred for eye-level predictors. - Averaging is suitable for subject-level predictors. - Statistical power was assessed across various sample sizes. - Generalized estimating equations showed elevated error rates in smaller samples. - Importance of model selection in avoiding misleading results. - No conflicts of interest reported by researchers.

Original Source(s)

Accounting for Eye Correlation Improves Statistical Accuracy

  • by Conexiant News Staff

  • March 23, 2026

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