Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (ROC) analysis in particular are important for assessing the performance of medical tests and statistical classifiers as well as for evaluating predictive models or algorithms. This book presents innovative approaches in ROC analysis which are relevant to a wide variety of applications including medical imaging cancer research epidemiology and bioinformatics. Statistical Evaluation of Diagnostic Performance: Topics in ROC Analysis covers areas including monotone-transformation techniques in parametric ROC analysis ROC methods for combined and pooled biomarkers Bayesian hierarchical transformation models sequential designs and inferences in the ROC setting predictive modeling multireader ROC analysis and free-response ROC (FROC) methodology. The book is suitable for graduate-level students and researchers in statistics biostatistics epidemiology public health biomedical engineering radiology medical imaging biomedical informatics and other closely related fields. Additionally clinical researchers and practicing statisticians in academia industry and government could benefit from the presentation of such important and yet frequently overlooked topics. . Language: English