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Titel: An Introduction to Generalized Linear Models...

Verlag: Chapman and Hall/CRC

Erscheinungsdatum: 2008

Einband: Softcover

Zustand: Good

Auflage: 3. Auflage

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Overall, this new edition remains a highly useful and compact introduction to a large number of seemingly disparate regression models. Depending on the background of the audience, it will be suitable for upper-level undergraduate or beginning post-graduate courses.
―Christian Kleiber, Statistical Papers (2012) 53

The comments of Lang in his review of the second edition, that ‘This relatively short book gives a nice introductory overview of the theory underlying generalized linear modelling. ...’ can equally be applied to the new edition. ... three new chapters on Bayesian analysis are also added. ... suitable for experienced professionals needing to refresh their knowledge ... .
―Pharmaceutical Statistics, 2011

The chapters are short and concise, and the writing is clear ... explanations are fundamentally sound and aimed well at an upper-level undergrad or early graduate student in a statistics-related field. This is a very worthwhile book: a good class text and a practical reference for applied statisticians.
―Biometrics

This book promises in its introductory section to provide a unifying framework for many statistical techniques. It accomplishes this goal easily. ... Furthermore, the text covers important topics that are frequently overlooked in introductory courses, such as models for ordinal outcomes. ... This book is an excellent resource, either as an introduction to or a reminder of the technical aspects of generalized linear models and provides a wealth of simple yet useful examples and data sets.
―Journal of Biopharmaceutical Statistics, Issue 2

Praise for the Second Edition:
The second edition ... is successful in filling a void in the otherwise sparse literature on the subject of generalized linear models at the introductory level ... a wide range of research applications are covered and ample workings are also provided to aid the reader in statistical calculations ... I would highly recommend this text ... .
―Kerrie Nelson, Statistics in Medicine, Vol. 23

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