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Bayesian Correction for Misclassification in Multilevel Count Data Models
Joint Authors
Song, Joon Jin
Nelson, Tyler
Chin, Yoo-Mi
Stamey, James D.
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-02-25
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Covariate misclassification is well known to yield biased estimates in single level regression models.
The impact on hierarchical count models has been less studied.
A fully Bayesian approach to modeling both the misclassified covariate and the hierarchical response is proposed.
Models with a single diagnostic test and with multiple diagnostic tests are considered.
Simulation studies show the ability of the proposed model to appropriately account for the misclassification by reducing bias and improving performance of interval estimators.
A real data example further demonstrated the consequences of ignoring the misclassification.
Ignoring misclassification yielded a model that indicated there was a significant, positive impact on the number of children of females who observed spousal abuse between their parents.
When the misclassification was accounted for, the relationship switched to negative, but not significant.
Ignoring misclassification in standard linear and generalized linear models is well known to lead to biased results.
We provide an approach to extend misclassification modeling to the important area of hierarchical generalized linear models.
American Psychological Association (APA)
Nelson, Tyler& Song, Joon Jin& Chin, Yoo-Mi& Stamey, James D.. 2018. Bayesian Correction for Misclassification in Multilevel Count Data Models. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-6.
https://search.emarefa.net/detail/BIM-1131901
Modern Language Association (MLA)
Nelson, Tyler…[et al.]. Bayesian Correction for Misclassification in Multilevel Count Data Models. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-6.
https://search.emarefa.net/detail/BIM-1131901
American Medical Association (AMA)
Nelson, Tyler& Song, Joon Jin& Chin, Yoo-Mi& Stamey, James D.. Bayesian Correction for Misclassification in Multilevel Count Data Models. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-6.
https://search.emarefa.net/detail/BIM-1131901
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1131901