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Small proportions: what to report for confidence intervals?
Author(s) -
Tobi Hilde,
van den Berg Paul B.,
de Jongvan den Berg Lolkje TW
Publication year - 2005
Publication title -
pharmacoepidemiology and drug safety
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.023
H-Index - 96
eISSN - 1099-1557
pISSN - 1053-8569
DOI - 10.1002/pds.1081
Subject(s) - confidence interval , medicine , pharmacoepidemiology , statistics , sample size determination , coverage probability , interval (graph theory) , mathematics , combinatorics , medical prescription , pharmacology
Purpose It is generally agreed that a confidence interval (CI) is usually more informative than a point estimate or p ‐value, but we rarely encounter small proportions with CI in the pharmacoepidemiological literature. When a CI is given it is sporadically reported, how it was calculated. This incorrectly suggests one single method to calculate CIs. To identify the method best suited for small proportions, seven approximate methods and the Clopper–Pearson Exact method to calculate CIs were compared. Methods In a simulation study for 90‐, 95‐ and 99%CIs, with sample size 1000 and proportions ranging from 0.001 to 0.01, were evaluated systematically. Main quality criteria were coverage and interval width. The methods are illustrated using data from pharmacoepidemiology studies. Results Simulations showed that standard Wald methods have insufficient coverage probability regardless of how the desired coverage is perceived. Overall, the Exact method and the Score method with continuity correction (CC) performed best. Real life examples showed the methods to yield different results too. Conclusions For CIs for small proportions ( π ≤ 0.01), the use of the Exact method and the Score method with CC are advocated based on this study. Copyright © 2005 John Wiley & Sons, Ltd.