Confidence interval construction for proportion difference from partially validated series with two fallible classifiers.

Autor: Qiu SF; Department of Statistics and Data Science, Chongqing University of Technology, Chongqing, China., Wang LM; Department of Statistics and Data Science, Chongqing University of Technology, Chongqing, China.; Chongqing Industry Polytechnic College, China., Tang ML; Department of Mathematics, Statistics and Insurance, Hang Seng University of Hong Kong, Hong Kong, China., Poon WY; Department of Statistics, The Chinese University of Hong Kong, Hong Kong, China.
Jazyk: angličtina
Zdroj: Journal of biopharmaceutical statistics [J Biopharm Stat] 2022 Nov 02; Vol. 32 (6), pp. 871-896. Date of Electronic Publication: 2022 May 10.
DOI: 10.1080/10543406.2022.2058527
Abstrakt: This article investigates the confidence interval (CI) construction of proportion difference for two independent partially validated series under the double-sampling scheme in which both classifiers are fallible. Several CIs based on the variance estimates recovery method of combining confidence limits from asymptotic, bootstrap, and Bayesian methods for two independent binomial proportions are developed under two models. Simulation results show that all CIs except for the bootstrap percentile-t CI and Bayesian credible interval with uniform prior under the independence model and all CIs under the dependence model generally perform well and are recommended. Two examples are used to illustrate the methodologies.
Databáze: MEDLINE
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