Statistical analysis measurement error di grace (23 risultati)

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    Hardcover. Condizione: Very Good. clean and sturdy copy, unmarked, no dj. jn.

  • Lingua: Inglese

    Editore: Springer New York, 2017

    1493966383 / 9781493966387

    Serie: Libro 147 di 160 - Springer Series in Statistics

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    Condizione: Hervorragend. Zustand: Hervorragend | Seiten: 508 | Sprache: Englisch | Produktart: Bücher | 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.

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  • Lingua: Inglese

    Editore: Springer, 2018

    1493982575 / 9781493982578

    Serie: Libro 147 di 160 - Springer Series in Statistics

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    Taschenbuch. 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.

  • Lingua: Inglese

    Editore: Springer, 2017

    1493966383 / 9781493966387

    Serie: Libro 147 di 160 - Springer Series in Statistics

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Buch. 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.

  • Lingua: Inglese

    Editore: Springer, 2018

    1493982575 / 9781493982578

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    Taschenbuch. Condizione: Neu. Statistical Analysis with Measurement Error or Misclassification | Strategy, Method and Application | Grace Y. Yi | Taschenbuch | Springer Series in Statistics | xxvii | Englisch | 2018 | Springer | EAN 9781493982578 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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  • Lingua: Inglese

    Editore: Springer Verlag, 2017

    1493966383 / 9781493966387

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. 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.

  • Lingua: Inglese

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    1493966383 / 9781493966387

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    Buch. 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.

  • Lingua: Inglese

    Editore: Springer New York, 2018

    1493982575 / 9781493982578

    Serie: Libro 147 di 160 - Springer Series in Statistics

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    Condizione: 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.

  • Lingua: Inglese

    Editore: Springer New York, 2017

    1493966383 / 9781493966387

    Serie: Libro 147 di 160 - Springer Series in Statistics

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    Condizione: 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.

  • Lingua: Inglese

    Editore: Springer, Springer US Aug 2018, 2018

    1493982575 / 9781493982578

    Serie: Libro 147 di 160 - Springer Series in Statistics

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    Taschenbuch. 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 KG, Sachsenplatz 4-6, 1201 Wien 508 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer, Springer US Aug 2017, 2017

    1493966383 / 9781493966387

    Serie: Libro 147 di 160 - Springer Series in Statistics

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    Buch. 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 KG, Sachsenplatz 4-6, 1201 Wien 508 pp. Englisch.

  • Lingua: Inglese

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    1493966383 / 9781493966387

    Serie: Libro 147 di 160 - Springer Series in Statistics

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    Condizione: New. Print on Demand pp. 487.

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    1493982575 / 9781493982578

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    1493966383 / 9781493966387

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    Hardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

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    1493982575 / 9781493982578

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