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Data Analysis Using Hierarchical Generalized Linear Models with R
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Data Analysis Using Hierarchical Generalized Linear Models with R Paperback - 2020

by Youngjo Lee; Lars Ronnegard; Maengseok Noh

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Reader reviews for Data Analysis Using Hierarchical Generalized Linear Models with R

From the publisher

Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models. Interest in the topic has grown, and various practical analytical tools have been developed. This book summarizes developments within the field and, using data examples, illustrates how to analyse various kinds of data using R. It provides a likelihood approach to advanced statistical modelling including generalized linear models with random effects, survival analysis and frailty models, multivariate HGLMs, factor and structural equation models, robust modelling of random effects, models including penalty and variable selection and hypothesis testing.

This example-driven book is aimed primarily at researchers and graduate students, who wish to perform data modelling beyond the frequentist framework, and especially for those searching for a bridge between Bayesian and frequentist statistics.

Details

  • Title Data Analysis Using Hierarchical Generalized Linear Models with R
  • Author Youngjo Lee; Lars Ronnegard; Maengseok Noh
  • Binding Paperback
  • Pages 322
  • Volumes 1
  • Language ENG
  • Publisher CRC Press
  • Publication date 2020-09-30
  • ISBN 9780367657925 / 0367657929
  • Category Mathematics
  • Dewey Decimal Code 519.5

About the author

Youngjo Lee is a professor in the department of Statistics at Seoul National University, Korea. His current research interests are extension, application, theory and software developments for HGLMs.

Lars Rnnegrd is affiliated with the Microdata Analysis group at Dalarna University, Sweden. His current research interests are applications of HGLMs in genetics and ecology, and computational aspects.

Maengseok Noh is a professor in the Department of Statistics at Pukyong National University, Korea. His current research interests are application and software developments for HGLMs.

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Data Analysis Using Hierarchical Generalized Linear Models with R

Data Analysis Using Hierarchical Generalized Linear Models with R

by Youngjo Lee

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Paperback / softback. New. Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models. Interest in the topic has grown, and various practical analytical tools have been developed. This book summarizes developments within the field and, using data examples, illustrates how to
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Data Analysis Using Hierarchical Generalized Linear Models with R

Data Analysis Using Hierarchical Generalized Linear Models with R

by Maengseok Noh

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Paperback / softback. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models. Interest in the topic has grown, and various practical analytical tools have
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Data Analysis Using Hierarchical Generalized Linear Models With R
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Data Analysis Using Hierarchical Generalized Linear Models With R

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Data Analysis Using Hierarchical Generalized Linear Models With R
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Data Analysis Using Hierarchical Generalized Linear Models With R

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Data Analysis Using Hierarchical Generalized Linear Models With R

by Youngjo Lee, Lars Ronnegard, Maengseok Noh,

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Data Analysis Using Hierarchical Generalized Linear Models with R
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Data Analysis Using Hierarchical Generalized Linear Models with R

by Lee, Youngjo

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