# Regression with Linear Predictors (Statistics for Biology and Health)

## Per Kragh Andersen; Lene Theil Skovgaard

0 valoración promedio
( 0 valoraciones por Goodreads )

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”.

"Sinopsis" puede pertenecer a otra edición de este libro.

From the Back Cover:

This text provides, in a non-technical language, a unified treatment of regression models for different outcome types, such as linear regression, logistic regression, and Cox regression. This is done by focusing on the many common aspects of these models, in particular the linear predictor, which combines the effects of all explanatory variables into a function which is linear in the unknown parameters. Specification and interpretation of various choices of parametrization of the effects of the covariates (categorical as well as quantitative) and interaction among these are elaborated upon. The merits and drawbacks of different link functions relating the linear predictor to the outcome are discussed with an emphasis on interpretational issues, and the fact that different research questions arise from adding or deleting covariates from the model is emphasized in both theory and practice. Regression models with a linear predictor are commonly used in fields such as clinical medicine, epidemiology, and public health, and the book, including its many worked examples, builds on the authors' more than thirty years of experience as teachers, researchers and consultants at a biostatistical department. The book is well-suited for readers without a solid mathematical background and is accompanied by Web pages documenting in R, SAS, and STATA, the analyses presented throughout the text. The authors are since 1978 affiliated with the Department of Biostatistics, University of Copenhagen. Per Kragh Andersen is professor; he is a co-author of the Springer book "Statistical Models Based on Counting Processes," and has served on editorial boards on several statistical journals. Lene Theil Skovgaard is associate professor; she has considerable experience as teacher and consultant, and has served on the editorial board of Biometrics.

The authors are since 1978 affiliated with the Department of Biostatistics, University of Copenhagen. Per Kragh Andersen is professor; he is a co-author of the Springer book "Statistical Models Based on Counting Processes," and has served on editorial boards on several statistical journals. Lene Theil Skovgaard is associate professor; she has considerable experience as teacher and consultant, and has served on the editorial board of Biometrics.

"Sobre este título" puede pertenecer a otra edición de este libro.

Comprar nuevo Ver libro
EUR 70,74

Gastos de envío: EUR 4,22
De Reino Unido a Estados Unidos de America

Destinos, gastos y plazos de envío

## 1.Regression with Linear Predictors

Editorial: Springer (2016)
ISBN 10: 1441971696 ISBN 13: 9781441971692
Impresión bajo demanda
Librería
Ria Christie Collections
(Uxbridge, Reino Unido)
Valoración

Descripción Springer, 2016. Paperback. Estado de conservación: New. PRINT ON DEMAND Book; New; Publication Year 2016; Not Signed; Fast Shipping from the UK. No. book. Nº de ref. de la librería ria9781441971692_lsuk

Comprar nuevo
EUR 70,74
Convertir moneda
Gastos de envío: EUR 4,22
De Reino Unido a Estados Unidos de America
Destinos, gastos y plazos de envío

## 2.Regression with Linear Predictors

Editorial: Springer (2010)
ISBN 10: 1441971696 ISBN 13: 9781441971692
Librería
Herb Tandree Philosophy Books
(Stroud, GLOS, Reino Unido)
Valoración

Descripción Springer, 2010. Hardback. Estado de conservación: NEW. 9781441971692 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Nº de ref. de la librería HTANDREE0298201

Comprar nuevo
EUR 66,25
Convertir moneda
Gastos de envío: EUR 8,72
De Reino Unido a Estados Unidos de America
Destinos, gastos y plazos de envío

## 3.Regression with Linear Predictors

Editorial: Springer-Verlag New York Inc. (2010)
ISBN 10: 1441971696 ISBN 13: 9781441971692
Impresión bajo demanda
Librería
Books2Anywhere
(Fairford, GLOS, Reino Unido)
Valoración

Descripción Springer-Verlag New York Inc., 2010. HRD. Estado de conservación: New. New Book. Delivered from our US warehouse in 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND.Established seller since 2000. Nº de ref. de la librería IP-9781441971692

Comprar nuevo
EUR 67,20
Convertir moneda
Gastos de envío: EUR 9,81
De Reino Unido a Estados Unidos de America
Destinos, gastos y plazos de envío

## 4.Regression with Linear Predictors

Editorial: Springer-Verlag New York Inc. (2010)
ISBN 10: 1441971696 ISBN 13: 9781441971692
Impresión bajo demanda
Librería
Pbshop
(Wood Dale, IL, Estados Unidos de America)
Valoración

Descripción Springer-Verlag New York Inc., 2010. HRD. Estado de conservación: New. New Book.Shipped from US within 10 to 14 business days.THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. de la librería IP-9781441971692

Comprar nuevo
EUR 78,75
Convertir moneda
Gastos de envío: EUR 3,39
Destinos, gastos y plazos de envío

## 5.Regression with Linear Predictors (Statistics for Biology and Health)

Editorial: Springer (2017)
ISBN 10: 1441971696 ISBN 13: 9781441971692
Impresión bajo demanda
Librería
Murray Media
(North Miami Beach, FL, Estados Unidos de America)
Valoración

Descripción Springer, 2017. Hardcover. Estado de conservación: New. Never used! This item is printed on demand. Nº de ref. de la librería 1441971696

Comprar nuevo
EUR 82,84
Convertir moneda
Gastos de envío: EUR 1,69
Destinos, gastos y plazos de envío

## 6.Regression with Linear Predictors (Statistics for Biology and Health)

Editorial: Springer (2010)
ISBN 10: 1441971696 ISBN 13: 9781441971692
Impresión bajo demanda
Librería
Ergodebooks
(RICHMOND, TX, Estados Unidos de America)
Valoración

Descripción Springer, 2010. Hardcover. Estado de conservación: New. 2010. This item is printed on demand. Nº de ref. de la librería DADAX1441971696

Comprar nuevo
EUR 83,88
Convertir moneda
Gastos de envío: EUR 3,39
Destinos, gastos y plazos de envío

## 7.Regression with Linear Predictors (Hardback)

Editorial: Springer-Verlag New York Inc., United States (2010)
ISBN 10: 1441971696 ISBN 13: 9781441971692
Impresión bajo demanda
Librería
The Book Depository
(London, Reino Unido)
Valoración

Descripción Springer-Verlag New York Inc., United States, 2010. Hardback. Estado de conservación: New. 2010 ed.. Language: English . Brand New Book ***** Print on Demand *****.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, 2x2, 2x(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 . Nº de ref. de la librería APC9781441971692

Comprar nuevo
EUR 90,35
Convertir moneda
Gastos de envío: GRATIS
De Reino Unido a Estados Unidos de America
Destinos, gastos y plazos de envío

## 8.Regression with Linear Predictors (Hardback)

Editorial: Springer-Verlag New York Inc., United States (2010)
ISBN 10: 1441971696 ISBN 13: 9781441971692
Impresión bajo demanda
Librería
The Book Depository US
(London, Reino Unido)
Valoración

Descripción Springer-Verlag New York Inc., United States, 2010. Hardback. Estado de conservación: New. 2010 ed.. Language: English . Brand New Book ***** Print on Demand *****. 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, 2x2, 2x(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 . Nº de ref. de la librería APC9781441971692

Comprar nuevo
EUR 90,71
Convertir moneda
Gastos de envío: GRATIS
De Reino Unido a Estados Unidos de America
Destinos, gastos y plazos de envío

## 9.Regression With Linear Predictors

ISBN 10: 1441971696 ISBN 13: 9781441971692
Impresión bajo demanda
Librería
BWB
(Valley Stream, NY, Estados Unidos de America)
Valoración

Descripción Estado de conservación: New. This item is Print on Demand - Depending on your location, this item may ship from the US or UK. Nº de ref. de la librería POD_9781441971692

Comprar nuevo
EUR 95,94
Convertir moneda
Gastos de envío: GRATIS
Destinos, gastos y plazos de envío

## 10.Regression with Linear Predictors (Statistics for Biology and Health)

Editorial: Springer (2017)
ISBN 10: 1441971696 ISBN 13: 9781441971692
Impresión bajo demanda
Librería
Murray Media
(North Miami Beach, FL, Estados Unidos de America)
Valoración

Descripción Springer, 2017. Hardcover. Estado de conservación: New. Never used! This item is printed on demand. Nº de ref. de la librería P111441971696

Comprar nuevo
EUR 103,48
Convertir moneda
Gastos de envío: EUR 1,69