Application of a Beta Regression Model for Covariate Adjusted ROC

Autor:	J.D. Tubbs, Xing Meng
Rok vydání:	2020
Předmět:	Generalized linear model Receiver operating characteristic Binary classification Covariate Parametric model Statistics Test performance Regression analysis General Medicine Beta distribution Mathematics
Zdroj:	Current Research in Biostatistics. 10:20-24
ISSN:	2524-2210
DOI:	10.3844/amjbsp.2020.20.24
Popis:	The Receiver Operating Characteristic (ROC) curve and the area under the ROC (AUC) are widely used in determining the diagnostic capability of a binary classification procedure. Since the test performance is affected by covariates, the ROC and AUC have been utilized in a Generalized Linear Regression (GLM) setting. In this study, we revisit a problem where the AUC regression model was used in a clinical study with discrete covariates by considering ROC regression models with both discrete and continuous covariates. The two ROC regression models are based upon a widely used parametric model and a recently published model based upon fitting the placement values with the beta distribution. The two methods are illustrated using data from a clinic study.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7762ff77f7fe703bdefb2462e8b44264 https://doi.org/10.3844/amjbsp.2020.20.24 Zobrazit plný text záznamu