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Title: | Estimation of Optimally Combined-Biomarker Accuracy in the Absence of a Gold Standard Reference Test | Authors: | GARCIA BARRADO, Leandro COART, Elisabeth BURZYKOWSKI, Tomasz |
Issue Date: | 2013 | Publisher: | Springer International Publishing | Source: | Lanzarone, Ettore; Ieva, Francesca (Ed.). The Contribution of Young Researchers to Bayesian Statistics: Proceedings of BAYSM2013, p. 7-10 | Series/Report: | Springer Proceedings in Mathematics & Statistics | Series/Report no.: | 63 | Abstract: | The reference diagnostic test used to establish the discriminative properties of a combination of biomarkers could be imperfect. This may lead to a biased estimate of the accuracy of the combination. A Bayesian latent-class mixture model is proposed to estimate the Area Under the ROC Curve (AUC) of a combination of biomarkers. The model allows selecting the combination that maximizes the AUC and takes possible errors in the reference test into account. A simulation study was performed based on 400 data sets. Sample sizes from 100 to 600 observations were considered. Informative as well as non-informative prior information for the diagnostic accuracy of the reference test was considered. In addition, a controlled prior specification is proposed. The obtained average estimates for all parameters were close to the true values; some differences in efficiency were observed. Results indicate an adequate performance of the model-based estimates. | Keywords: | Bayesian estimation; latent class mixture models; AUC | Document URI: | http://hdl.handle.net/1942/16164 | ISBN: | 978-3-319-02084-6 | DOI: | 10.1007/978-3-319-02084-6 | Category: | C1 | Type: | Proceedings Paper |
Appears in Collections: | Research publications |
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