Simplifying the estimation of diagnostic testing accuracy over time for high specificity tests in the absence of a gold standard
Clara Drew,
Moses Badio,
Dehkontee Dennis,
Lisa Hensley,
Elizabeth Higgs,
Michael Sneller,
Mosoka Fallah and
Cavan Reilly
Biometrics, 2023, vol. 79, issue 2, 1546-1558
Abstract:
Many different methods for evaluating diagnostic test results in the absence of a gold standard have been proposed. In this paper, we discuss how one common method, a maximum likelihood estimate for a latent class model found via the Expectation‐Maximization (EM) algorithm can be applied to longitudinal data where test sensitivity changes over time. We also propose two simplified and nonparametric methods which use data‐based indicator variables for disease status and compare their accuracy to the maximum likelihood estimation (MLE) results. We find that with high specificity tests, the performance of simpler approximations may be just as high as the MLE.
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1111/biom.13689
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:biomet:v:79:y:2023:i:2:p:1546-1558
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0006-341X
Access Statistics for this article
More articles in Biometrics from The International Biometric Society
Bibliographic data for series maintained by Wiley Content Delivery ().