9781461426271 - regression with linear predictors (statistics for biology and health) di andersen, per kragh (16 risultati)

Lingua: Inglese
Editore: Springer 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
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Lingua: Inglese
Editore: Springer 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
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Lingua: Inglese
Editore: Springer 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
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Lingua: Inglese
Editore: Springer 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
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Lingua: Inglese
Editore: Springer 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
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Condizione: New. pp. 508.

Lingua: Inglese
Editore: Springer 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
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Lingua: Inglese
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Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
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Lingua: Inglese
Editore: Springer 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
- Brossura
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Condizione: New. pp. 508 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

Lingua: Inglese
Editore: Springer-Verlag New York Inc. 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
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Altre immaginiLingua: Inglese
Editore: Springer 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
- Brossura
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Taschenbuch. Condizione: Neu. Regression with Linear Predictors | Per Kragh Andersen (u. a.) | Taschenbuch | Statistics for Biology and Health | ix | Englisch | 2012 | Springer | EAN 9781461426271 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]…com | Anbieter: preigu.

Lingua: Inglese
Editore: Springer New York, Springer US 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
- Brossura
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: 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'.

Lingua: Inglese
Editore: Springer 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
- Brossura
- Print on Demand
Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.

Lingua: Inglese
Editore: Springer New York Sep 2012 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
- Brossura
- Print on Demand
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 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 for the other explanatory variables in the model 'held xed'. 508 pp. Englisch.

Lingua: Inglese
Editore: Springer 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
- Brossura
- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND pp. 508.

Lingua: Inglese
Editore: Springer New York 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
- Brossura
- Print on Demand
Da: moluna, Greven, Germaniamoluna
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Condizione: 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 .

Lingua: Inglese
Editore: Springer, Copernicus Sep 2012 2012
Serie: Statistics for Biology and Health, Libro 39 di 69. Libro 39 di 69 - Statistics for Biology and Health
- Brossura
- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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-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¿.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 508 pp. Englisch.