Author: James K. Lindsey
Publisher:
ISBN: 9780198508120
Category : Mathematics
Languages : en
Pages : 298
Book Description
This text provides an introduction to the use of nonlinear models in medical statistics. It is a practical text rather than a theoretical one and assumes a basic knowledge of statistical modelling and of generalized linear models. It begins with a general introduction to nonlinear models, comparing them to generalized linear models, descriptions of data handling and formula definition and a summary of the principal types of nonlinear regression formulae. There is an emphasis on techniques for non-normal data. Following chapters provide detailed examples of applications in various areas of medicine, epidemiology, clinical trials, quality of life, pharmokinetics, pharmacodynamics, assays and formulations, and moleuclar genetics.
Nonlinear Models in Medical Statistics
Author: James K. Lindsey
Publisher:
ISBN: 9780198508120
Category : Mathematics
Languages : en
Pages : 298
Book Description
This text provides an introduction to the use of nonlinear models in medical statistics. It is a practical text rather than a theoretical one and assumes a basic knowledge of statistical modelling and of generalized linear models. It begins with a general introduction to nonlinear models, comparing them to generalized linear models, descriptions of data handling and formula definition and a summary of the principal types of nonlinear regression formulae. There is an emphasis on techniques for non-normal data. Following chapters provide detailed examples of applications in various areas of medicine, epidemiology, clinical trials, quality of life, pharmokinetics, pharmacodynamics, assays and formulations, and moleuclar genetics.
Publisher:
ISBN: 9780198508120
Category : Mathematics
Languages : en
Pages : 298
Book Description
This text provides an introduction to the use of nonlinear models in medical statistics. It is a practical text rather than a theoretical one and assumes a basic knowledge of statistical modelling and of generalized linear models. It begins with a general introduction to nonlinear models, comparing them to generalized linear models, descriptions of data handling and formula definition and a summary of the principal types of nonlinear regression formulae. There is an emphasis on techniques for non-normal data. Following chapters provide detailed examples of applications in various areas of medicine, epidemiology, clinical trials, quality of life, pharmokinetics, pharmacodynamics, assays and formulations, and moleuclar genetics.
Fitting Models to Biological Data Using Linear and Nonlinear Regression
Author: Harvey Motulsky
Publisher: Oxford University Press
ISBN: 9780198038344
Category : Mathematics
Languages : en
Pages : 352
Book Description
Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.
Publisher: Oxford University Press
ISBN: 9780198038344
Category : Mathematics
Languages : en
Pages : 352
Book Description
Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.
Linear and Nonlinear Models for the Analysis of Repeated Measurements
Author: Edward Vonesh
Publisher: CRC Press
ISBN: 9780824782481
Category : Mathematics
Languages : en
Pages : 590
Book Description
Integrates the latest theory, methodology and applications related to the design and analysis of repeated measurement. The text covers a broad range of topics, including the analysis of repeated measures design, general crossover designs, and linear and nonlinear regression models. It also contains a 3.5 IBM compatible disk, with software to implement immediately the techniques.
Publisher: CRC Press
ISBN: 9780824782481
Category : Mathematics
Languages : en
Pages : 590
Book Description
Integrates the latest theory, methodology and applications related to the design and analysis of repeated measurement. The text covers a broad range of topics, including the analysis of repeated measures design, general crossover designs, and linear and nonlinear regression models. It also contains a 3.5 IBM compatible disk, with software to implement immediately the techniques.
Statistical Tools for Nonlinear Regression
Author: Sylvie Huet
Publisher: Springer Science & Business Media
ISBN: 147572523X
Category : Mathematics
Languages : en
Pages : 161
Book Description
Statistical Tools for Nonlinear Regression presents methods for analyzing data. It has been expanded to include binomial, multinomial and Poisson non-linear models. The examples are analyzed with the free software nls2 updated to deal with the new models included in the second edition. The nls2 package is implemented in S-PLUS and R. Several additional tools are included in the package for calculating confidence regions for functions of parameters or calibration intervals, using classical methodology or bootstrap.
Publisher: Springer Science & Business Media
ISBN: 147572523X
Category : Mathematics
Languages : en
Pages : 161
Book Description
Statistical Tools for Nonlinear Regression presents methods for analyzing data. It has been expanded to include binomial, multinomial and Poisson non-linear models. The examples are analyzed with the free software nls2 updated to deal with the new models included in the second edition. The nls2 package is implemented in S-PLUS and R. Several additional tools are included in the package for calculating confidence regions for functions of parameters or calibration intervals, using classical methodology or bootstrap.
Nonlinear Regression with R
Author: Christian Ritz
Publisher: Springer Science & Business Media
ISBN: 0387096167
Category : Mathematics
Languages : en
Pages : 151
Book Description
- Coherent and unified treatment of nonlinear regression with R. - Example-based approach. - Wide area of application.
Publisher: Springer Science & Business Media
ISBN: 0387096167
Category : Mathematics
Languages : en
Pages : 151
Book Description
- Coherent and unified treatment of nonlinear regression with R. - Example-based approach. - Wide area of application.
Optimal Design for Nonlinear Response Models
Author: Valerii V. Fedorov
Publisher: CRC Press
ISBN: 1439821526
Category : Mathematics
Languages : en
Pages : 398
Book Description
Optimal Design for Nonlinear Response Models discusses the theory and applications of model-based experimental design with a strong emphasis on biopharmaceutical studies. The book draws on the authors' many years of experience in academia and the pharmaceutical industry. While the focus is on nonlinear models, the book begins with an explanation of
Publisher: CRC Press
ISBN: 1439821526
Category : Mathematics
Languages : en
Pages : 398
Book Description
Optimal Design for Nonlinear Response Models discusses the theory and applications of model-based experimental design with a strong emphasis on biopharmaceutical studies. The book draws on the authors' many years of experience in academia and the pharmaceutical industry. While the focus is on nonlinear models, the book begins with an explanation of
Nonlinear Regression Analysis and Its Applications
Author: Douglas M. Bates
Publisher: Wiley-Interscience
ISBN:
Category : Mathematics
Languages : en
Pages : 398
Book Description
Provides a presentation of the theoretical, practical, and computational aspects of nonlinear regression. There is background material on linear regression, including a geometrical development for linear and nonlinear least squares.
Publisher: Wiley-Interscience
ISBN:
Category : Mathematics
Languages : en
Pages : 398
Book Description
Provides a presentation of the theoretical, practical, and computational aspects of nonlinear regression. There is background material on linear regression, including a geometrical development for linear and nonlinear least squares.
Regression Models as a Tool in Medical Research
Author: Werner Vach
Publisher: CRC Press
ISBN: 1466517484
Category : Mathematics
Languages : en
Pages : 497
Book Description
While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the results is often challenging for beginners. Regression Models as a Tool in Medical Research presents the fundamental concepts and important aspects of regression models most commonly used in medical research, including the classical regression model for continuous outcomes, the logistic regression model for binary outcomes, and the Cox proportional hazards model for survival data. The text emphasizes adequate use, correct interpretation of results, appropriate presentation of results, and avoidance of potential pitfalls. After reviewing popular models and basic methods, the book focuses on advanced topics and techniques. It considers the comparison of regression coefficients, the selection of covariates, the modeling of nonlinear and nonadditive effects, and the analysis of clustered and longitudinal data, highlighting the impact of selection mechanisms, measurement error, and incomplete covariate data. The text then covers the use of regression models to construct risk scores and predictors. It also gives an overview of more specific regression models and their applications as well as alternatives to regression modeling. The mathematical details underlying the estimation and inference techniques are provided in the appendices.
Publisher: CRC Press
ISBN: 1466517484
Category : Mathematics
Languages : en
Pages : 497
Book Description
While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the results is often challenging for beginners. Regression Models as a Tool in Medical Research presents the fundamental concepts and important aspects of regression models most commonly used in medical research, including the classical regression model for continuous outcomes, the logistic regression model for binary outcomes, and the Cox proportional hazards model for survival data. The text emphasizes adequate use, correct interpretation of results, appropriate presentation of results, and avoidance of potential pitfalls. After reviewing popular models and basic methods, the book focuses on advanced topics and techniques. It considers the comparison of regression coefficients, the selection of covariates, the modeling of nonlinear and nonadditive effects, and the analysis of clustered and longitudinal data, highlighting the impact of selection mechanisms, measurement error, and incomplete covariate data. The text then covers the use of regression models to construct risk scores and predictors. It also gives an overview of more specific regression models and their applications as well as alternatives to regression modeling. The mathematical details underlying the estimation and inference techniques are provided in the appendices.
Bayesian Methods for Nonlinear Classification and Regression
Author: David G. T. Denison
Publisher: John Wiley & Sons
ISBN: 9780471490364
Category : Mathematics
Languages : en
Pages : 302
Book Description
Bei der Regressionsanalyse von Datenmaterial erhält man leider selten lineare oder andere einfache Zusammenhänge (parametrische Modelle). Dieses Buch hilft Ihnen, auch komplexere, nichtparametrische Modelle zu verstehen und zu beherrschen. Stärken und Schwächen jedes einzelnen Modells werden durch die Anwendung auf Standarddatensätze demonstriert. Verbreitete nichtparametrische Modelle werden mit Hilfe von Bayes-Verfahren in einen kohärenten wahrscheinlichkeitstheoretischen Zusammenhang gebracht.
Publisher: John Wiley & Sons
ISBN: 9780471490364
Category : Mathematics
Languages : en
Pages : 302
Book Description
Bei der Regressionsanalyse von Datenmaterial erhält man leider selten lineare oder andere einfache Zusammenhänge (parametrische Modelle). Dieses Buch hilft Ihnen, auch komplexere, nichtparametrische Modelle zu verstehen und zu beherrschen. Stärken und Schwächen jedes einzelnen Modells werden durch die Anwendung auf Standarddatensätze demonstriert. Verbreitete nichtparametrische Modelle werden mit Hilfe von Bayes-Verfahren in einen kohärenten wahrscheinlichkeitstheoretischen Zusammenhang gebracht.
Mixed Effects Models for Complex Data
Author: Lang Wu
Publisher: CRC Press
ISBN: 1420074083
Category : Mathematics
Languages : en
Pages : 436
Book Description
Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors,
Publisher: CRC Press
ISBN: 1420074083
Category : Mathematics
Languages : en
Pages : 436
Book Description
Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors,