EconPapers    
Economics at your fingertips  
 

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 ().

 
Page updated 2025-03-19
Handle: RePEc:bla:biomet:v:79:y:2023:i:2:p:1546-1558