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Chapman and Hall/Crc Biostatistics Ser.: ROC Analysis for Classification and Prediction in Practice by Constantine A. Gatsonis, Christos T. Nakas and Leonidas E. Bantis (2023, Hardcover)

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About this product

Product Identifiers

PublisherCRC Press LLC

ISBN-101482233703

ISBN-139781482233704

eBay Product ID (ePID)20061243316

Product Key Features

Number of Pages218 Pages

LanguageEnglish

Publication NameRoc Analysis for Classification and Prediction in Practice

Publication Year2023

SubjectBiostatistics, Probability & Statistics / General, General

TypeTextbook

AuthorConstantine A. Gatsonis, Christos T. Nakas, Leonidas E. Bantis

Subject AreaMathematics, Medical

SeriesChapman and Hall/Crc Biostatistics Ser.

FormatHardcover

Dimensions

Item Weight14.9 Oz

Item Length9.2 in

Item Width6.1 in

Additional Product Features

Intended AudienceScholarly & Professional

LCCN2022-055093

Reviews"This book fills a critical gap. I could not find another reference on the ROC curve as comprehensive as the one by Nakas, Bantis, and Gatsonis. This book should be recommended as an excellent reference textbook for anyone needing an in-depth understanding of the ROC curve or for a specialized graduate course." - Mauricio Tec , Journal of the American Statistical Association

Dewey Edition23/eng20230506

IllustratedYes

Dewey Decimal519.2/87

Table Of Content1. Introduction 2. Measures of Diagnostic and Predictive Performance 3. Statistical inference for the ROC curve 4. Comparing ROC curves 5. The ROC surface and k-class classification for k > 2 6. ROC regression 7. Missing data and errors-in-variables in ROC analysis

SynopsisThis book presents a unified and up-to date introduction to ROC methodologies, covering both diagnosis (classification) and prediction. It emphasizes the practical implementation of these methods using standard statistical software such as R and STATA. Existing books tend to be specialized and/or focus on the theoretical derivations, with limited discussion of the use of the concepts and methods across diverse scientific fields and modest emphasis on the implementation of the methods., This book will present a unified and up-to date introduction to ROC methodologies, covering both diagnosis (classification) and prediction. The book will emphasize the practical implementation of these methods using standard statistical software such as R and STATA., This book presents a unified and up-to-date introduction to ROC methodologies, covering both diagnosis (classification) and prediction. The emphasis is on the conceptual underpinning of ROC analysis and the practical implementation in diverse scientific fields. A plethora of examples accompany the methodologic discussion using standard statistical software such as R and STATA. The book arrives after two decades of intensive growth in both the methods and the applications of ROC analysis and presents a new synthesis. The authors provide a contemporary, integrated exposition of ROC methodology for both classification and prediction and include material on multiple-class ROC. This book avoids lengthy technical exposition and provides code and datasets in each chapter. ROC Analysis for Classification and Prediction in Practice is intended for researchers and graduate students, but will also be useful for those that use ROC analysis in diverse disciplines such as diagnostic medicine, bioinformatics, medical physics, and perception psychology.

LC Classification NumberQA279.2.N35 2023