Youngjo Lee, Lars Ronnegard, Maengseok Noh

Data Analysis Using Hierarchical Generalized Linear Models with R (eBook, PDF)

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 334
• Erscheinungstermin: 6. Juli 2017
• Englisch
• ISBN-13: 9781351811569
• Artikelnr.: 48802812

Autorenporträt

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 Rönnegård 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.