Synopsis
During the last decades, there has been an explosion in computation and information technology. This development comes with an expansion of complex observational studies and clinical trials in a variety of fields such as medicine, biology, epidemiology, sociology, and economics among many others, which involve collection of large amounts of data on subjects or organisms over time. This book provides a fundamental statistical framework for the analysis of this type of data.
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Unified Methods for Censored Longitudinal Data and Causality (Springer Series in Statistics)
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Springer, 2011
ISBN 10 : 1441930558
ISBN 13 : 9781441930552
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Etat : good. This is a pre-loved book that shows moderate signs of wear from previous reading. You may notice creases, edge wear, or a cracked spine, but it remains in solid, readable condition.Please note:-May include library or rental stickers, stamps, or markings.-Supplemental materials e.g., CDs, access codes, inserts are not guaranteed.-Box sets may not come with the original outer box. If it does, the box will not be in perfect condition. -Sourced from donation centers; authenticity not verified with publisher. Your satisfaction is our top priority! If you have any questions or concerns about your order, please don't hesitate to reach out. Thank you for shopping with us and supporting small businessâ"happy reading! N° de réf. du vendeur STM.EPM
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Unified Methods for Censored Longitudinal Data and Causality (Springer Series in Statistics)
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Unified Methods for Censored Longitudinal Data and Causality (Springer Series in Statistics)
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Unified Methods for Censored Longitudinal Data and Causality
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Springer New York Mai 2011, 2011
ISBN 10 : 1441930558
ISBN 13 : 9781441930552
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A fundamental statistical framework for the analysis of complex longitudinal data is provided in this book. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures. The techniques go beyond standard statistical approaches and can be used to teach masters and Ph.D. students. The text is ideally suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data. 412 pp. Englisch. N° de réf. du vendeur 9781441930552
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Unified Methods for Censored Longitudinal Data and Causality
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Springer New York, 2011
ISBN 10 : 1441930558
ISBN 13 : 9781441930552
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. During the last decades, there has been an explosion in computation and information technology. This development comes with an expansion of complex observational studies and clinical trials in a variety of fields such as medicine, biology, epidemiology, soc. N° de réf. du vendeur 4173516
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Unified Methods for Censored Longitudinal Data and Causality
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Taschenbuch. Etat : Neu. Unified Methods for Censored Longitudinal Data and Causality | James M Robins (u. a.) | Taschenbuch | xii | Englisch | 2011 | Humana | EAN 9781441930552 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 107252908
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Unified Methods for Censored Longitudinal Data and Causality
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Unified Methods for Censored Longitudinal Data and Causality
Edité par
Springer New York, Springer US Mai 2011, 2011
ISBN 10 : 1441930558
ISBN 13 : 9781441930552
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -During the last decades, there has been an explosion in computation and information technology. This development comes with an expansion of complex observational studies and clinical trials in a variety of fields such as medicine, biology, epidemiology, sociology, and economics among many others, which involve collection of large amounts of data on subjects or organisms over time. The goal of such studies can be formulated as estimation of a finite dimensional parameter of the population distribution corresponding to the observed time- dependent process. Such estimation problems arise in survival analysis, causal inference and regression analysis. This book provides a fundamental statistical framework for the analysis of complex longitudinal data. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures subject to informative censoring and treatment assignment in so called semiparametric models. Semiparametric models are particularly attractive since they allow the presence of large unmodeled nuisance parameters. These techniques include estimation of regression parameters in the familiar (multivariate) generalized linear regression and multiplicative intensity models. They go beyond standard statistical approaches by incorporating all the observed data to allow for informative censoring, to obtain maximal efficiency, and by developing estimators of causal effects. It can be used to teach masters and Ph.D. students in biostatistics and statistics and is suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 412 pp. Englisch. N° de réf. du vendeur 9781441930552
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Unified Methods for Censored Longitudinal Data and Causality
Edité par
Springer New York, Springer US, 2011
ISBN 10 : 1441930558
ISBN 13 : 9781441930552
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - During the last decades, there has been an explosion in computation and information technology. This development comes with an expansion of complex observational studies and clinical trials in a variety of fields such as medicine, biology, epidemiology, sociology, and economics among many others, which involve collection of large amounts of data on subjects or organisms over time. The goal of such studies can be formulated as estimation of a finite dimensional parameter of the population distribution corresponding to the observed time- dependent process. Such estimation problems arise in survival analysis, causal inference and regression analysis. This book provides a fundamental statistical framework for the analysis of complex longitudinal data. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures subject to informative censoring and treatment assignment in so called semiparametric models. Semiparametric models are particularly attractive since they allow the presence of large unmodeled nuisance parameters. These techniques include estimation of regression parameters in the familiar (multivariate) generalized linear regression and multiplicative intensity models. They go beyond standard statistical approaches by incorporating all the observed data to allow for informative censoring, to obtain maximal efficiency, and by developing estimators of causal effects. It can be used to teach masters and Ph.D. students in biostatistics and statistics and is suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data. N° de réf. du vendeur 9781441930552
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Etat : New. Print on Demand pp. 412 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam. N° de réf. du vendeur 11289436
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