Isbn: 9789811099670 - analysis of repeated measures data (16 resultados)

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    Editorial: Springer, 2018

    9811099677 / 9789811099670

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    Condición: New. In English.

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  • Idioma: Inglés

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  • Idioma: Inglés

    Editorial: Springer, 2018

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    Paperback. Condición: Brand New. reprint edition. 250 pages. 9.25x6.10x0.62 inches. In Stock.

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    Idioma: Inglés

    Editorial: Springer, 2018

    9811099677 / 9789811099670

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    Taschenbuch. Condición: Neu. Analysis of Repeated Measures Data | M. Ataharul Islam (u. a.) | Taschenbuch | xix | Englisch | 2018 | Springer | EAN 9789811099670 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Idioma: Inglés

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a broad range of statistical techniques to address emerging needs in the field of repeated measures. It also provides a comprehensive overview of extensions of generalized linear models for the bivariate exponential family of distributions, which represent a new development in analysing repeated measures data. The demand for statistical models for correlated outcomes has grown rapidly recently, mainly due to presence of two types of underlying associations: associations between outcomes, and associations between explanatory variables and outcomes.The book systematically addresses key problems arising in the modelling of repeated measures data, bearing in mind those factors that play a major role in estimating the underlying relationships between covariates and outcome variables for correlated outcome data. In addition, it presents new approaches to addressing current challenges in the field of repeated measures and models based on conditional and joint probabilities. Markov models of first and higher orders are used for conditional models in addition to conditional probabilities as a function of covariates. Similarly, joint models are developed using both marginal-conditional probabilities as well as joint probabilities as a function of covariates.In addition to generalized linear models for bivariate outcomes, it highlights extended semi-parametric models for continuous failure time data and their applications in order to include models for a broader range of outcome variables that researchers encounter in various fields. The book further discusses the problem of analysing repeated measures data for failure time in the competing risk framework, which is now taking on an increasingly important role in the field of survival analysis, reliability and actuarial science. Details on how to perform the analyses are included in each chapter and supplemented with newly developed R packages and functions along with SAS codes and macro/IML. It is a valuable resource for researchers, graduate students and other users of statistical techniques for analysing repeated measures data.

  • Idioma: Inglés

    Editorial: Springer, 2018

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    Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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  • Idioma: Inglés

    Editorial: Springer Nature Singapore Mai 2018, 2018

    9811099677 / 9789811099670

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a broad range of statistical techniques to address emerging needs in the field of repeated measures. It also provides a comprehensive overview of extensions of generalized linear models for the bivariate exponential family of distributions, which represent a new development in analysing repeated measures data. The demand for statistical models for correlated outcomes has grown rapidly recently, mainly due to presence of two types of underlying associations: associations between outcomes, and associations between explanatory variables and outcomes.The book systematically addresses key problems arising in the modelling of repeated measures data, bearing in mind those factors that play a major role in estimating the underlying relationships between covariates and outcome variables for correlated outcome data. In addition, it presents new approaches to addressing current challenges in the field of repeated measures and models based on conditional and joint probabilities. Markov models of first and higher orders are used for conditional models in addition to conditional probabilities as a function of covariates. Similarly, joint models are developed using both marginal-conditional probabilities as well as joint probabilities as a function of covariates.In addition to generalized linear models for bivariate outcomes, it highlights extended semi-parametric models for continuous failure time data and their applications in order to include models for a broader range of outcome variables that researchers encounter in various fields. The book further discusses the problem of analysing repeated measures data for failure time in the competing risk framework, which is now taking on an increasingly important role in the field of survival analysis, reliability and actuarial science. Details on how to perform the analyses are included in each chapter and supplemented with newly developed R packages and functions along with SAS codes and macro/IML. It is a valuable resource for researchers, graduate students and other users of statistical techniques for analysing repeated measures data. 272 pp. Englisch.

  • Idioma: Inglés

    Editorial: Springer, 2018

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    Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books

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    Condición: New. Print on Demand pp. 250.

  • Idioma: Inglés

    Editorial: Springer, 2018

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  • Idioma: Inglés

    Editorial: Springer Singapore, 2018

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    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Addresses the challenges involved in analyzing repeated-measures data in real-life situations with models applicable to a wide range of correlated outcome variables&nbspCovers not only traditional marginal models but also new approaches based on .

  • Idioma: Inglés

    Editorial: Springer, Springer Mai 2018, 2018

    9811099677 / 9789811099670

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents a broad range of statistical techniques to address emerging needs in the field of repeated measures. It also provides a comprehensive overview of extensions of generalized linear models for the bivariate exponential family of distributions, which represent a new development in analysing repeated measures data. The demand for statistical models for correlated outcomes has grown rapidly recently, mainly due to presence of two types of underlying associations: associations between outcomes, and associations between explanatory variables and outcomes.The book systematically addresses key problems arising in the modelling of repeated measures data, bearing in mind those factors that play a major role in estimating the underlying relationships between covariates and outcome variables for correlated outcome data. In addition, it presents new approaches to addressing current challenges in the field of repeated measures and models based on conditional and joint probabilities. Markov models of first and higher orders are used for conditional models in addition to conditional probabilities as a function of covariates. Similarly, joint models are developed using both marginal-conditional probabilities as well as joint probabilities as a function of covariates.In addition to generalized linear models for bivariate outcomes, it highlights extended semi-parametric models for continuous failure time data and their applications in order to include models for a broader range of outcome variables that researchers encounter in various fields. The book further discusses the problem of analysing repeated measures data for failure time in the competing risk framework, which is now taking on an increasingly important role in the field of survival analysis, reliability and actuarial science. Details on how to perform the analyses are included in each chapter and supplemented with newly developed R packages and functions along with SAS codes and macro/IML. It is a valuable resource for researchers, graduate students and other users of statistical techniques for analysing repeated measures data.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 272 pp. Englisch.