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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: Books Puddle, New York, NY, Estados Unidos de America
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Añadir al carritoCondición: New. pp. 508.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 59,97
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This is a book about regression analysis, that is, the situation in statistics where the distribution of a response (or outcome) variable is related to - planatory variables (or covariates). This is an extremely common situation in the application of statistical methods in many elds, andlinear regression,- gistic regression, and Cox proportional hazards regression are frequently used for quantitative, binary, and survival time outcome variables, respectively. Several books on these topics have appeared and for that reason one may well ask why we embark on writing still another book on regression. We have two main reasons for doing this: 1. First, we want to highlightsimilaritiesamonglinear,logistic,proportional hazards,andotherregressionmodelsthatincludealinearpredictor. These modelsareoftentreatedentirelyseparatelyintextsinspiteofthefactthat alloperationsonthemodelsdealingwiththelinearpredictorareprecisely the same, including handling of categorical and quantitative covariates, testing for linearity and studying interactions. 2. Second, we want to emphasize that, for any type of outcome variable, multiple regression models are composed of simple building blocks that areaddedtogetherinthelinearpredictor:thatis,t-tests,one-wayanalyses of variance and simple linear regressions for quantitative outcomes, 2×2, 2×(k+1) tables and simple logistic regressions for binary outcomes, and 2-and (k+1)-sample logrank testsand simple Cox regressionsfor survival data. Thishastwoconsequences. Allthesesimpleandwellknownmethods can be considered as special cases of the regression models. On the other hand, the e ect of a single explanatory variable in a multiple regression model can be interpreted in a way similar to that obtained in the simple analysis, however, now valid only forthe other explanatory variables in the model 'held xed'.
Librería: Antiquariat am Flughafen, Berlin, Alemania
EUR 45,00
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Añadir al carritoHardcover. Hardcover. gr. 8°. XI, 494 pages. with 171 figures. good condition in englischer Sprache (in english).
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
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Librería: Basi6 International, Irving, TX, Estados Unidos de America
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Añadir al carritoCondición: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.
Idioma: Inglés
Publicado por SPRINGER NATURE Jul 2010, 2010
ISBN 10: 1441971696 ISBN 13: 9781441971692
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 53,49
Cantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This is a book about regression analysis, that is, the situation in statistics where the distribution of a response (or outcome) variable is related to - planatory variables (or covariates). This is an extremely common situation in the application of statistical methods in many elds, andlinear regression,- gistic regression, and Cox proportional hazards regression are frequently used for quantitative, binary, and survival time outcome variables, respectively. Several books on these topics have appeared and for that reason one may well ask why we embark on writing still another book on regression. We have two main reasons for doing this: 1. First, we want to highlightsimilaritiesamonglinear,logistic,proportional hazards,andotherregressionmodelsthatincludealinearpredictor. These modelsareoftentreatedentirelyseparatelyintextsinspiteofthefactthat alloperationsonthemodelsdealingwiththelinearpredictorareprecisely the same, including handling of categorical and quantitative covariates, testing for linearity and studying interactions. 2. Second, we want to emphasize that, for any type of outcome variable, multiple regression models are composed of simple building blocks that areaddedtogetherinthelinearpredictor:thatis,t-tests,one-wayanalys es of variance and simple linear regressions for quantitative outcomes, 2×2, 2×(k+1) tables and simple logistic regressions for binary outcomes, and 2-and (k+1)-sample logrank testsand simple Cox regressionsfor survival data. Thishastwoconsequences. Allthesesimpleandwellknownmethods can be considered as special cases of the regression models. On the other hand, the e ect of a single explanatory variable in a multiple regression model can be interpreted in a way similar to that obtained in the simple analysis, however, now valid only for the other explanatory variables in the model 'held xed'. 494 pp. Englisch.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 85,45
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Añadir al carritoCondición: New. Print on Demand pp. 508 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 87,12
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 508.
Librería: moluna, Greven, Alemania
EUR 48,74
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Añadir al carritoGebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Highlights similarities between regression models for quantitative, binary and survival time outcomes through construction of a linear predictor and emphasizes interpretation of effects and reparametrizationsIncludes worked examples from authors .