Modelling Frequency and Count Data

J. K. Lindsey

ISBN 10: 0198523319 / ISBN 13: 9780198523314

Published by Oxford University Press, GB, 1995

About this Item

Categorical data analysis is a special area of generalised linear models, which has become the most important area of statistical applications in many disciplines, from medicine to social sciences. This text presents the standard models and many newly developed ones in a language which can be immediately applied in many modern statistical packages such as GLIM, GENSTAT, S-Plus, as well as SAS and LISP-STAT. The book is structure around the distinction between independent events occurring to different individuals, resulting in frequencies, and repeated events occurring to the same individuals, yielding counts. The book demonstates that much of modern statistics can be seen as special cases of categorical data models; both generalized linear models and proportional hazards models can be fitted as log linear models. More specialized topics such as Markov chains, overdispersion and random effects, are also covered.

Seller Inventory # LU-9780198523314

Bibliographic Details

• Title: Modelling Frequency and Count Data
• Publisher: Oxford University Press, GB
• Publication Date: 1995
• Language: English
• ISBN 10: 0198523319
• ISBN 13: 9780198523314
• Binding: Hardback
• Condition: New
• Weight: 607 grams

About this title

Synopsis

Categorical data analysis is a special area of generalized linear models, which has become the most important area of statistical applications in many disciplines, from medicine to social sciences. This text presents the standard models and many newly developed ones in a language that can be immediately applied in many modern statistical packages such as GLIM, GENSTAT, S-Plus, as well as SAS and LISP-STAT. The book is structure around the distinction between independent events occurring to different individuals, resulting in frequencies, and repeated events occurring to the same individuals, yielding counts. The book demonstrates that much of modern statistics can be seen as special cases of categorical data models; both generalized linear models and proportional hazards models can be fitted as log linear models. More specialized topics such as Markov chains, overdispersion and random effects, are also covered.

About the Author

J. K. Lindsey is at University of Liege.