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Analyzing Receiver Operating Characteristic Curves with SAS

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Gonen, Mithat

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Analyzing Receiver Operating Characteristic Curves with SAS, ISBN 9781599942988 Own This Book? Sell It
ISBN-13:

9781599942988

ISBN:

1599942984

Pub Date: 2007
Publisher: SAS Publishing Summary: Analyzing Receiver Operating Characteristic Curves with SAS As a diagnostic decision-making tool, receiver operating characteristic (ROC) curves provide a comprehensive and visually attractive way to summarize the accuracy of predictions. They are extensively used in medical diagnosis and increasingly in fields such as data mining, credit scoring, weather forecasting, and psychometry. In this example-driven book, aut [read more]
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Product Details
ISBN-13:

9781599942988


ISBN:

1599942984


Pub Date: 2007
Publisher: SAS Publishing

Analyzing Receiver Operating Characteristic Curves with SAS As a diagnostic decision-making tool, receiver operating characteristic (ROC) curves provide a comprehensive and visually attractive way to summarize the accuracy of predictions. They are extensively used in medical diagnosis and increasingly in fields such as data mining, credit scoring, weather forecasting, and psychometry. In this example-driven book, author Mithat Gonen illustrates the many existing SAS procedures that can be tailored to produce ROC curves and expands upon further analyses using other SAS procedures and macros. Both parametric and nonparametric methods for analyzing ROC curves are covered in detail. Topics addressed include: Appropriate methods for binary, ordinal, and continuous measures Computations using PROC FREQ, PROC LOGISTIC, PROC NLMIXED, and macros Comparing the ROC curves of several markers and adjusting them for covariates ROC curves with censored data Using the ROC curve for evaluating multivariable prediction models via the bootstrap and cross-validation ROC curves in SAS Enterprise Miner And more! Written for any statistician interested in learning more about ROC curve methodology, the book assumes readers have a basic understanding of regression procedures and moderate familiarity with Base SAS and SAS/STAT. Some familiarity with SAS/GRAPH is helpful but not essential.

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