WAN-YU LINWEN-CHUNG LEE2020-11-192020-11-1920121932-6203https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857415370&doi=10.1371%2fjournal.pone.0032022&partnerID=40&md5=ccd92332363b0a448e8a20598be82e16https://scholars.lib.ntu.edu.tw/handle/123456789/521844Quantifying exposure-disease associations is a central issue in epidemiology. Researchers of a study often present an odds ratio (or a logarithm of odds ratio, logOR) estimate together with its confidence interval (CI), for each exposure they examined. Here the authors advocate using the empirical-Bayes-based 'prediction intervals' (PIs) to bound the uncertainty of logORs. The PI approach is applicable to a panel of factors believed to be exchangeable (no extra information, other than the data itself, is available to distinguish some logORs from the others). The authors demonstrate its use in a genetic epidemiological study on age-related macular degeneration (AMD). The proposed PIs can enjoy straightforward probabilistic interpretations-a 95% PI has a probability of 0.95 to encompass the true value, and the expected number of true values that are being encompassed is 0:95m for a total of m 95% PIs. The PI approach is theoretically more efficient (producing shorter intervals) than the traditional CI approach. In the AMD data, the average efficiency gain is 51.2%. The PI approach is advocated to present the uncertainties of many logORs in a study, for its straightforward probabilistic interpretations and higher efficiency while maintaining the nominal coverage probability.English[SDGs]SDG3article; Bayes theorem; confidence interval; controlled study; disease association; exposure; genetic epidemiology; odd ratio; prediction interval; probability; retina macula age related degeneration; simulation; single nucleotide polymorphism; statistical analysis; statistical concepts; statistical model; uncertainty; Bayes theorem; biological model; computer simulation; genetics; human; retina macula degeneration; risk; Bayes Theorem; Computer Simulation; Confidence Intervals; Humans; Macular Degeneration; Models, Genetic; Odds Ratio; Uncertaintyjournal article10.1371/journal.pone.0032022223637892-s2.0-84857415370