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Paperback. Condition: New. Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for clinicians, epidemiologists, and professional statisticians who need to make or evaluate a statistical prediction model based on data. The subject of the book is the patient's individualized probability of a medical event within a given time horizon. Gerds and Kattan describe the mathematical details of making and evaluating a statistical prediction model in a highly pedagogical manner while avoiding mathematical notation. Read this book when you are in doubt about whether a Cox regression model predicts better than a random survival forest.Features:All you need to know to correctly make an online risk calculator from scratch. Discrimination, calibration, and predictive performance with censored data and competing risks. R-code and illustrative examples. Interpretation of prediction performance via benchmarks. Comparison and combination of rival modeling strategies via cross-validation.
Language: English
Published by Chapman and Hall/CRC, 2022
ISBN 10: 0367673738 ISBN 13: 9780367673734
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Published by Chapman and Hall/CRC, 2022
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Kartoniert / Broschiert. Condition: New. Thomas A. Gerds is professor at the biostatistics unit at the University of Copenhagen. He is affiliated with the Danish Heart Foundation. He is author of several R-packages on CRAN and has taught statistics courses to non-statisticians .
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Published by Chapman and Hall/CRC, 2022
ISBN 10: 0367673738 ISBN 13: 9780367673734
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Taschenbuch. Condition: Neu. Medical Risk Prediction Models | With Ties to Machine Learning | Thomas A. Gerds (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2022 | Chapman and Hall/CRC | EAN 9780367673734 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Published by Taylor and Francis Ltd, GB, 2022
ISBN 10: 0367673738 ISBN 13: 9780367673734
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Add to basketPaperback. Condition: New. Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for clinicians, epidemiologists, and professional statisticians who need to make or evaluate a statistical prediction model based on data. The subject of the book is the patient's individualized probability of a medical event within a given time horizon. Gerds and Kattan describe the mathematical details of making and evaluating a statistical prediction model in a highly pedagogical manner while avoiding mathematical notation. Read this book when you are in doubt about whether a Cox regression model predicts better than a random survival forest.Features:All you need to know to correctly make an online risk calculator from scratch. Discrimination, calibration, and predictive performance with censored data and competing risks. R-code and illustrative examples. Interpretation of prediction performance via benchmarks. Comparison and combination of rival modeling strategies via cross-validation.
Language: English
Published by Routledge 2021-02-01, 2021
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