Clinical Ophthalmology (Jul 2024)
Statistical Methods for Best and Worst Eye Measurements
Abstract
Kaustav Banerjee,1 Subhasish Pramanik,2 Lakshmi Kanta Mondal3 1Decision Sciences Area, Indian Institute of Management Lucknow, Uttar Pradesh, 226013, India; 2Department of Endocrinology & Metabolism, Institute of Post Graduate Medical Education & Research and SSKM Hospital, Kolkata, West Bengal, 700020, India; 3Department of Ophthalmology, Regional Institute of Ophthalmology, Medical College Campus, Kolkata, West Bengal, 700073, IndiaCorrespondence: Lakshmi Kanta Mondal, Department of Ophthalmology, Regional Institute of Ophthalmology, Medical College Campus, Kolkata, West Bengal, 700073, India, Tel +9830830216, Email [email protected]: The focus is often on the best and worst eyes to detect early predictive and non-invasive biomarkers of diabetic retinopathy. Typically, such data have been dealt with in a case-control setting, which applies two-sample tests and ignores the correlation between the fellow eyes. Practitioners are mostly unaware that such measurements hide the labels of the fellow eyes, which rules out standard tools, such as paired t or signed-rank tests.Methods: This report discusses the problems with such data on best and worst eye measurements, and illustrates alternative paired tests for equality of means or locations using a case-control dataset.Results: This report illustrates that methods which ignore the correlation between fellow eyes result in grossly conservative tests. A battery of Z-tests which consider this correlation can resolve this issue.Discussion: This finding emphasizes the importance of selecting an appropriate control group for the detection of possible markers. Further, it cites an example to show that using data from fellow eyes and adjusting for their correlation may not always be the best option, contrary to common perception.Keywords: best eye, worst eye, unordered pairs
