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A note on modeling placement values in the analysis of receiver operating characteristic curves

A note on modeling placement values in the analysis of receiver operating characteristic curves Recent advances in receiver operating characteristic (ROC) curve analyses advocate modeling of placement value (PV), a quantity that measures the position of diseased test scores relative to the healthy population. Compared to traditional approaches, this PV-based alternative works directly with ROC curves and is attractive when assessing covariate effects on, or incorporating a priori constraints of, ROC curves. Several distributions can be used to model the PV, yet little guidelines exist in the literature on which to use. Through extensive simulation studies, we investigate several parametric models for PV when data are generated from a variety of mechanisms. We discuss the pros and cons of each of these models and illustrate their applications with data from a study of prenatal ultrasound examinations and large-for-gestational age birth. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biostatistics & Epidemiology Taylor & Francis

A note on modeling placement values in the analysis of receiver operating characteristic curves

Biostatistics & Epidemiology , Volume 5 (2): 16 – Jul 3, 2021

A note on modeling placement values in the analysis of receiver operating characteristic curves

Abstract

Recent advances in receiver operating characteristic (ROC) curve analyses advocate modeling of placement value (PV), a quantity that measures the position of diseased test scores relative to the healthy population. Compared to traditional approaches, this PV-based alternative works directly with ROC curves and is attractive when assessing covariate effects on, or incorporating a priori constraints of, ROC curves. Several distributions can be used to model the PV, yet little guidelines exist...
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/lp/taylor-francis/a-note-on-modeling-placement-values-in-the-analysis-of-receiver-Ewtrqe1O8T
Publisher
Taylor & Francis
Copyright
© 2020 International Biometric Society – Chinese Region
ISSN
2470-9379
eISSN
2470-9360
DOI
10.1080/24709360.2020.1737794
Publisher site
See Article on Publisher Site

Abstract

Recent advances in receiver operating characteristic (ROC) curve analyses advocate modeling of placement value (PV), a quantity that measures the position of diseased test scores relative to the healthy population. Compared to traditional approaches, this PV-based alternative works directly with ROC curves and is attractive when assessing covariate effects on, or incorporating a priori constraints of, ROC curves. Several distributions can be used to model the PV, yet little guidelines exist in the literature on which to use. Through extensive simulation studies, we investigate several parametric models for PV when data are generated from a variety of mechanisms. We discuss the pros and cons of each of these models and illustrate their applications with data from a study of prenatal ultrasound examinations and large-for-gestational age birth.

Journal

Biostatistics & EpidemiologyTaylor & Francis

Published: Jul 3, 2021

Keywords: AUC; ROC; diagnostic accuracy; large for gestational age; beta regression

References