Statistical Evaluation of Diagnostic Performance
Topics in ROC Analysis
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An important method for statistical validation is the receiver operating characteristic (ROC) analysis. This visual tool is used in a variety of clinical areas, including laboratory testing, epidemiology, radiology, and bioinformatics, for evaluating diagnostic tests. This book gives a historical overview of the empirical and nonparametric ROC method for continuous diagnostic and classification data. It introduces methods for estimating and comparing ROC curves based on diagnostic test results and covers both semiparametric and parametric models. The authors develop likelihood-based algorithm...
An important method for statistical validation is the receiver operating characteristic (ROC) analysis. This visual tool is used in a variety of clinical areas, including laboratory testing, epidemiology, radiology, and bioinformatics, for evaluating diagnostic tests. This book gives a historical overview of the empirical and nonparametric ROC method for continuous diagnostic and classification data. It introduces methods for estimating and comparing ROC curves based on diagnostic test results and covers both semiparametric and parametric models. The authors develop likelihood-based algorithms for estimating an ROC curve and its characteristics under these models. They also present methods for sample size calculations and Monte Carlo simulations. The text includes many real clinical examples, with R code provided for all of them.
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