Confidence limits for prevalence of disease adjusted for estimated sensitivity and specificity

作     者：Lang, Zsolt Reiczigel, Jeno 

作者机构：Szent Istvan Univ Fac Vet Sci H-1078 Budapest Hungary 

出 版 物：《PREVENTIVE VETERINARY MEDICINE》 (预防兽医学)

年 卷 期：2014年第113卷第1期

页      面：13-22页

核心收录：

学科分类：0906[农学-兽医学] 09[农学] 

基　　金：TAMOP-4.2.2.B-10/1 TAMOP-4.2.1.B-11/2/KMR-2011-0003 OTKA K108571 

主　　题：Imperfect diagnostic test Binomial confidence interval Coverage probability False positives False negatives Exact and approximate inference 

摘      要：Prevalence of a disease is usually assessed by diagnostic tests that may produce false results. Rogan and Gladen (1978) described a method to estimate the true prevalence correcting for sensitivity and specificity of the diagnostic procedure, and Reiczigel et al. (2010) provided exact confidence intervals for the true prevalence assuming sensitivity and specificity were known. In this paper we propose a new method to construct approximate confidence intervals for the true prevalence when sensitivity and specificity are estimated from independent samples. To improve coverage we applied an adjustment similar to that described in Agresti and Coull (1998). According to an extensive simulation study the new confidence intervals maintain the nominal level fairly well even for sample sizes as small as 30;minimum coverage is above 88%, 93%, and 98% at nominal 90%, 95%, and 99%, respectively. We illustrate the advantages of the proposed method with real-life applications. (C) 2013 Elsevier B.V. All rights reserved.