Da: Amazing Books Pittsburgh, Pittsburgh, PA, U.S.A.
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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: Best Price, Torrance, CA, U.S.A.
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Editore: Springer-Verlag New York Inc., New York, 2017
ISBN 10: 1493966383 ISBN 13: 9781493966387
Lingua: Inglese
Da: Grand Eagle Retail, Mason, OH, U.S.A.
Prima edizione
EUR 160,73
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems.Readers with diverse backgrounds and objectives can utilize this text. Familiarity with inference methodssuch as likelihood and estimating function theoryor modeling schemes in varying settingssuch as survival analysis and longitudinal data analysiscan result in a full appreciation of the material, but it is not essential since each chapter provides basic inference frameworks and background information on an individual topic to ease the access of the material. The text is presented in a coherent and self-contained manner and highlights the essence of commonly used modeling and inference methods.This text can serve as a reference book for researchers interested in statistical methodology for handling data with measurement error or misclassification; as a textbook for graduate students, especially for those majoring in statistics and biostatistics; or as a book for applied statisticians whose interest focuses on analysis of error-contaminated data.Grace Y. Yi is Professor of Statistics and University Research Chair at the University of Waterloo. She is the 2010 winner of the CRM-SSC Prize, an honor awarded in recognition of a statistical scientist's professional accomplishments in research during the first 15 years after having received a doctorate. She is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 157,25
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Da: Ria Christie Collections, Uxbridge, Regno Unito
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Da: California Books, Miami, FL, U.S.A.
EUR 177,21
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Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 184,14
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Editore: Springer-Verlag New York Inc., 2017
ISBN 10: 1493966383 ISBN 13: 9781493966387
Lingua: Inglese
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 198,67
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Aggiungi al carrelloCondizione: New. Series: Springer Series in Statistics. Num Pages: 487 pages, 15 black & white illustrations, 1 colour illustrations, biography. BIC Classification: MBNS; PBT; PBWH; PSA. Category: (P) Professional & Vocational. Dimension: 235 x 155. . . 2017. Hardback. . . . .
Da: Buchpark, Trebbin, Germania
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Aggiungi al carrelloCondizione: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher.
Editore: Springer New York, Springer US Aug 2017, 2017
ISBN 10: 1493966383 ISBN 13: 9781493966387
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 160,49
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware -This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 508 pp. Englisch.
Editore: Springer New York, Springer US, 2017
ISBN 10: 1493966383 ISBN 13: 9781493966387
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 164,49
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems.Readers with diverse backgrounds and objectives can utilize this text. Familiarity with inference methods-such as likelihood and estimating function theory-or modeling schemes in varying settings-such as survival analysis and longitudinal data analysis-can result in a full appreciation of the material, but it is not essential since each chapter provides basic inference frameworks and background information on an individual topic to ease the access of the material. The text is presented in a coherent and self-contained manner and highlights the essence of commonly used modeling and inference methods.This text can serve as a reference book for researchers interested in statistical methodology for handling data with measurement error or misclassification; as a textbook for graduate students, especially for those majoring in statistics and biostatistics; or as a book for applied statisticians whose interest focuses on analysis of error-contaminated data.Grace Y. Yi is Professor of Statistics and University Research Chair at the University of Waterloo. She is the 2010 winner of the CRM-SSC Prize, an honor awarded in recognition of a statistical scientist's professional accomplishments in research during the first 15 years after having received a doctorate. She is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute.
Editore: Springer New York, Springer New York, 2018
ISBN 10: 1493982575 ISBN 13: 9781493982578
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 166,62
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems.Readers with diverse backgrounds and objectives can utilize this text. Familiarity with inference methods-such as likelihood and estimating function theory-or modeling schemes in varying settings-such as survival analysis and longitudinal data analysis-can result in a full appreciation of the material, but it is not essential since each chapter provides basic inference frameworks and background information on an individual topic to ease the access of the material. The text is presented in a coherent and self-contained manner and highlights the essence of commonly used modeling and inference methods.This text can serve as a reference book for researchers interested in statistical methodology for handling data with measurement error or misclassification; as a textbook for graduate students, especially for those majoring in statistics and biostatistics; or as a book for applied statisticians whose interest focuses on analysis of error-contaminated data.Grace Y. Yi is Professor of Statistics and University Research Chair at the University of Waterloo. She is the 2010 winner of the CRM-SSC Prize, an honor awarded in recognition of a statistical scientist's professional accomplishments in research during the first 15 years after having received a doctorate. She is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute.
Editore: Springer-Verlag New York Inc., 2017
ISBN 10: 1493966383 ISBN 13: 9781493966387
Lingua: Inglese
Da: Kennys Bookstore, Olney, MD, U.S.A.
EUR 247,35
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Aggiungi al carrelloCondizione: New. Series: Springer Series in Statistics. Num Pages: 487 pages, 15 black & white illustrations, 1 colour illustrations, biography. BIC Classification: MBNS; PBT; PBWH; PSA. Category: (P) Professional & Vocational. Dimension: 235 x 155. . . 2017. Hardback. . . . . Books ship from the US and Ireland.
Editore: Springer-Verlag New York Inc., New York, 2017
ISBN 10: 1493966383 ISBN 13: 9781493966387
Lingua: Inglese
Da: AussieBookSeller, Truganina, VIC, Australia
Prima edizione
EUR 230,94
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems.Readers with diverse backgrounds and objectives can utilize this text. Familiarity with inference methodssuch as likelihood and estimating function theoryor modeling schemes in varying settingssuch as survival analysis and longitudinal data analysiscan result in a full appreciation of the material, but it is not essential since each chapter provides basic inference frameworks and background information on an individual topic to ease the access of the material. The text is presented in a coherent and self-contained manner and highlights the essence of commonly used modeling and inference methods.This text can serve as a reference book for researchers interested in statistical methodology for handling data with measurement error or misclassification; as a textbook for graduate students, especially for those majoring in statistics and biostatistics; or as a book for applied statisticians whose interest focuses on analysis of error-contaminated data.Grace Y. Yi is Professor of Statistics and University Research Chair at the University of Waterloo. She is the 2010 winner of the CRM-SSC Prize, an honor awarded in recognition of a statistical scientist's professional accomplishments in research during the first 15 years after having received a doctorate. She is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Da: Revaluation Books, Exeter, Regno Unito
EUR 236,64
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Aggiungi al carrelloHardcover. Condizione: Brand New. 1st edition. 479 pages. 9.50x6.25x1.25 inches. In Stock.
Editore: Springer New York Aug 2018, 2018
ISBN 10: 1493982575 ISBN 13: 9781493982578
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 160,49
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems.Readers with diverse backgrounds and objectives can utilize this text. Familiarity with inference methods-such as likelihood and estimating function theory-or modeling schemes in varying settings-such as survival analysis and longitudinal data analysis-can result in a full appreciation of the material, but it is not essential since each chapter provides basic inference frameworks and background information on an individual topic to ease the access of the material. The text is presented in a coherent and self-contained manner and highlights the essence of commonly used modeling and inference methods.This text can serve as a reference book for researchers interested in statistical methodology for handling data with measurement error or misclassification; as a textbook for graduate students, especially for those majoring in statistics and biostatistics; or as a book for applied statisticians whose interest focuses on analysis of error-contaminated data.Grace Y. Yi is Professor of Statistics and University Research Chair at the University of Waterloo. She is the 2010 winner of the CRM-SSC Prize, an honor awarded in recognition of a statistical scientist's professional accomplishments in research during the first 15 years after having received a doctorate. She is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute. 508 pp. Englisch.
Editore: Springer New York Aug 2017, 2017
ISBN 10: 1493966383 ISBN 13: 9781493966387
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 160,49
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems.Readers with diverse backgrounds and objectives can utilize this text. Familiarity with inference methods-such as likelihood and estimating function theory-or modeling schemes in varying settings-such as survival analysis and longitudinal data analysis-can result in a full appreciation of the material, but it is not essential since each chapter provides basic inference frameworks and background information on an individual topic to ease the access of the material. The text is presented in a coherent and self-contained manner and highlights the essence of commonly used modeling and inference methods.This text can serve as a reference book for researchers interested in statistical methodology for handling data with measurement error or misclassification; as a textbook for graduate students, especially for those majoring in statistics and biostatistics; or as a book for applied statisticians whose interest focuses on analysis of error-contaminated data.Grace Y. Yi is Professor of Statistics and University Research Chair at the University of Waterloo. She is the 2010 winner of the CRM-SSC Prize, an honor awarded in recognition of a statistical scientist's professional accomplishments in research during the first 15 years after having received a doctorate. She is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute. 508 pp. Englisch.
Da: moluna, Greven, Germania
EUR 136,16
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Brings together assorted methods concerning measurement error or misclassification in a single text, including updates of recent developments for a variety of settingsPresents both statistical theory and applications in a cohe.
Da: moluna, Greven, Germania
EUR 136,16
Convertire valutaQuantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Brings together assorted methods concerning measurement error or misclassification in a single text, including updates of recent developments for a variety of settingsPresents both statistical theory and applications in a cohe.
Editore: Springer New York, Springer New York Aug 2018, 2018
ISBN 10: 1493982575 ISBN 13: 9781493982578
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 160,49
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 508 pp. Englisch.
Editore: Springer-Verlag New York Inc., 2017
ISBN 10: 1493966383 ISBN 13: 9781493966387
Lingua: Inglese
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 211,63
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Aggiungi al carrelloHardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 1238.