Multivariate generalized linear mixed models using R / Damon M. Berridge, Robert Crouchley.

Format:

Book

Author/Creator:

Berridge, Damon M., author.

Contributor:

Crouchley, Robert.

Language:

English

Subjects (All):

R (Computer program language).

Social sciences--Research--Mathematical models.

Social sciences.

Social sciences--Research--Statistical methods.

Social sciences--Research--Data processing.

Multivariate analysis.

Physical Description:

1 online resource (284 p.)

Edition:

1st ed.

Place of Publication:

Boca Raton, Fla. : CRC Press, c2011.

Boca Raton, Fla. : CRC Press, 2011.

Language Note:

English

Summary:

To provide researchers with the ability to analyze large and complex data sets using robust models, this book presents a unified framework for a broad class of models that can be applied using a dedicated R package (Sabre). The first five chapters cover the analysis of multilevel models using univariate generalized linear mixed models (GLMMs). The next few chapters extend to multivariate GLMMs and the last chapters address more specialized topics, such as parallel computing for large-scale analyses. Each chapter includes many real-world examples implemented using Sabre as well as exercises and

Contents:

Front Cover; Contents; List of Figures; List of Tables; List of Applications; List of Datasets; Preface; Acknowledgments; 1. Introduction; 2.Generalized linear models for continuous/interval scale data; 3. Generalized linear models for other types of data; 4. Family of generalized linear models; 5. Mixed models for continuous/interval scale data; 6. Mixed models for binary data; 7. Mixed models for ordinal data; 8. Mixed models for count data; 9. Family of two-level generalized linear models; 10. Three-level generalized linear models; 11. Models for multivariate data

12. Models for duration and event history data13. Stayers, non-susceptibles and endpoints; 14. Handling initial conditions/state dependence in binary data; 15. Incidental parameters: an empirical comparison of fixed effects and random effects models; A. SabreR installation, SabreR commands, quadrature, estimation, endogenous effects; B. Introduction to R for Sabre; References

Notes:

A Chapman & Hall book.

Includes bibliographical references and indexes.

Description based on metadata supplied by the publisher and other sources.

ISBN:

9781040079140

1040079148

9780429191602

042919160X

9781498740708

1498740707

9781439813270

1439813272

OCLC:

756675740