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J Biopharm Stat. 2016;26(3):421-31. doi: 10.1080/10543406.2015.1052479. Epub 2015 May 26.

Binary classification using multivariate receiver operating characteristic curve for continuous data.

Author information

1
a Department of Statistics , Pondicherry University , Pondicherry , India.
2
b Department of Statistics , Sri Venkateswara University , Tirupati , India.

Abstract

The classification scenario needs handling of more than one biomarker. The main objective of the work is to propose a multivariate receiver operating characteristic (MROC) model which linearly combines the markers to classify them into one of the two groups and also to determine an optimal cut point. Simulation studies are conducted for four sets of mean vectors and covariance matrices and a real dataset is also used to demonstrate the proposed model. Linear and quadratic discriminant analysis has also been applied to the above datasets in order to explain the ease of the proposed model. Bootstrapped estimates of the parameters of the ROC curve are also estimated.

KEYWORDS:

AUC; MROC; Optimal cutoff

PMID:
26010331
DOI:
10.1080/10543406.2015.1052479
[Indexed for MEDLINE]

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