Simplifying the estimation of diagnostic testing accuracy over time for high specificity tests in the absence of a gold standard
Author
Abstract
Suggested Citation
DOI: 10.1111/biom.13689
Download full text from publisher
References listed on IDEAS
- Huiping Xu & Bruce A. Craig, 2009. "A Probit Latent Class Model with General Correlation Structures for Evaluating Accuracy of Diagnostic Tests," Biometrics, The International Biometric Society, vol. 65(4), pages 1145-1155, December.
- Chinyereugo M Umemneku Chikere & Kevin Wilson & Sara Graziadio & Luke Vale & A Joy Allen, 2019. "Diagnostic test evaluation methodology: A systematic review of methods employed to evaluate diagnostic tests in the absence of gold standard – An update," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-25, October.
- Paul S. Albert & Lori E. Dodd, 2004. "A Cautionary Note on the Robustness of Latent Class Models for Estimating Diagnostic Error without a Gold Standard," Biometrics, The International Biometric Society, vol. 60(2), pages 427-435, June.
- Grün, Bettina & Leisch, Friedrich, 2008. "FlexMix Version 2: Finite Mixtures with Concomitant Variables and Varying and Constant Parameters," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i04).
- Paul S. Albert & Lisa M. McShane & Joanna H. Shih, 2001. "Latent Class Modeling Approaches for Assessing Diagnostic Error without a Gold Standard: With Applications to p53 Immunohistochemical Assays in Bladder Tumors," Biometrics, The International Biometric Society, vol. 57(2), pages 610-619, June.
- Chu, Haitao & Chen, Sining & Louis, Thomas A., 2009. "Random Effects Models in a Meta-Analysis of the Accuracy of Two Diagnostic Tests Without a Gold Standard," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 512-523.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Bruce D. Spencer, 2012. "When Do Latent Class Models Overstate Accuracy for Diagnostic and Other Classifiers in the Absence of a Gold Standard?," Biometrics, The International Biometric Society, vol. 68(2), pages 559-566, June.
- Paul S. Albert, 2007. "Random Effects Modeling Approaches for Estimating ROC Curves from Repeated Ordinal Tests without a Gold Standard," Biometrics, The International Biometric Society, vol. 63(2), pages 593-602, June.
- Chinyereugo M Umemneku Chikere & Kevin Wilson & Sara Graziadio & Luke Vale & A Joy Allen, 2019. "Diagnostic test evaluation methodology: A systematic review of methods employed to evaluate diagnostic tests in the absence of gold standard – An update," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-25, October.
- Liu, Wei & Zhang, Bo & Zhang, Zhiwei & Chen, Baojiang & Zhou, Xiao-Hua, 2015. "A pseudo-likelihood approach for estimating diagnostic accuracy of multiple binary medical tests," Computational Statistics & Data Analysis, Elsevier, vol. 84(C), pages 85-98.
- Wang, Zheyu & Sebestyen, Krisztian & Monsell, Sarah E., 2017. "Model-based clustering for assessing the prognostic value of imaging biomarkers and mixed type tests," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 125-135.
- Bo Zhang & Zhen Chen & Paul S. Albert, 2012. "Estimating Diagnostic Accuracy of Raters Without a Gold Standard by Exploiting a Group of Experts," Biometrics, The International Biometric Society, vol. 68(4), pages 1294-1302, December.
- Elizabeth R. Brown, 2010. "Bayesian Estimation of the Time-Varying Sensitivity of a Diagnostic Test with Application to Mother-to-Child Transmission of HIV," Biometrics, The International Biometric Society, vol. 66(4), pages 1266-1274, December.
- Pankaj Patel & Sherry Thatcher & Katerina Bezrukova, 2013. "Organizationally-relevant configurations: the value of modeling local dependence," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 287-311, January.
- Donal O'Neill & Olive Sweetman, 2013.
"Estimating Obesity Rates in Europe in the Presence of Self-Reporting Errors,"
Economics Department Working Paper Series
n236-13.pdf, Department of Economics, National University of Ireland - Maynooth.
- O'Neill, Donal & Sweetman, Olive, 2013. "Estimating Obesity Rates in the Presence of Measurement Error," IZA Discussion Papers 7288, Institute of Labor Economics (IZA).
- Christian Kleiber & Achim Zeileis, 2016.
"Visualizing Count Data Regressions Using Rootograms,"
The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 296-303, July.
- Christian Kleiber & Achim Zeileis, 2014. "Visualizing Count Data Regressions Using Rootograms," Working Papers 2014-20, Faculty of Economics and Statistics, Universität Innsbruck.
- Kleiber, Christian & Zeileis, Achim, 2014. "Visualizing Count Data Regressions Using Rootograms," Working papers 2014/13, Faculty of Business and Economics - University of Basel.
- Lebret, Rémi & Iovleff, Serge & Langrognet, Florent & Biernacki, Christophe & Celeux, Gilles & Govaert, Gérard, 2015. "Rmixmod: The R Package of the Model-Based Unsupervised, Supervised, and Semi-Supervised Classification Mixmod Library," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i06).
- Nandini Dendukuri & Ian Schiller & Lawrence Joseph & Madhukar Pai, 2012. "Bayesian Meta-Analysis of the Accuracy of a Test for Tuberculous Pleuritis in the Absence of a Gold Standard Reference," Biometrics, The International Biometric Society, vol. 68(4), pages 1285-1293, December.
- Grün, Bettina & Kosmidis, Ioannis & Zeileis, Achim, 2012.
"Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned,"
Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i11).
- Bettina Grün & Ioannis Kosmidis & Achim Zeileis, 2011. "Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned," Working Papers 2011-22, Faculty of Economics and Statistics, Universität Innsbruck.
- Marc A. Scott & Kaushik Mohan & Jacques‐Antoine Gauthier, 2020. "Model‐based clustering and analysis of life history data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1231-1251, June.
- M. Battisti & F. Belloc & M. Del Gatto, 2017.
"Technology-specific Production Functions,"
Working Paper CRENoS
201709, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
- Michele Battisti & Filippo Belloc & Massimo Del Gatto, 2017. "Technology-specific Production Functions," Working Paper series 17-26, Rimini Centre for Economic Analysis.
- Friederike Paetz & Winfried J. Steiner, 2017. "The benefits of incorporating utility dependencies in finite mixture probit models," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 793-819, July.
- Lluís Bermúdez & Dimitris Karlis & Isabel Morillo, 2020. "Modelling Unobserved Heterogeneity in Claim Counts Using Finite Mixture Models," Risks, MDPI, vol. 8(1), pages 1-13, January.
- Salvatore Ingrassia & Antonio Punzo & Giorgio Vittadini & Simona Minotti, 2015. "Erratum to: The Generalized Linear Mixed Cluster-Weighted Model," Journal of Classification, Springer;The Classification Society, vol. 32(2), pages 327-355, July.
- Frick, Hannah & Strobl, Carolin & Leisch, Friedrich & Zeileis, Achim, 2012.
"Flexible Rasch Mixture Models with Package psychomix,"
Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i07).
- Hannah Frick & Carolin Strobl & Friedrich Leisch & Achim Zeileis, 2011. "Flexible Rasch Mixture Models with Package psychomix," Working Papers 2011-21, Faculty of Economics and Statistics, Universität Innsbruck.
- O’Neill, Donal, 2015.
"Measuring obesity in the absence of a gold standard,"
Economics & Human Biology, Elsevier, vol. 17(C), pages 116-128.
- Donal O'Neill, 2013. "Measuring Obesity in the Absence of a Gold Standard," Economics Department Working Paper Series n247-13b.pdf, Department of Economics, National University of Ireland - Maynooth.
- O'Neill, Donal, 2014. "Measuring Obesity in the Absence of a Gold Standard," IZA Discussion Papers 7893, Institute of Labor Economics (IZA).
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:biomet:v:79:y:2023:i:2:p:1546-1558. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.