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Introduction to mixed modelling : beyond regression and analysis of variance

Author: Nick Galwey; Wiley InterScience (Online service)
Publisher: Chichester, England ; Hoboken, NJ : Wiley, ©2006.
Edition/Format:   eBook : Document : EnglishView all editions and formats
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Mixed modelling is one of the most promising and exciting areas of statistical analysis, enabling more powerful interpretation of data through the recognition of random effects. However, many  Read more...

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Genre/Form: Electronic books
Additional Physical Format: Print version:
Galwey, Nick.
Introduction to mixed modelling.
Chichester, England ; Hoboken, NJ : Wiley, ©2006
(DLC) 2006023991
(OCoLC)70707837
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Nick Galwey; Wiley InterScience (Online service)
ISBN: 9780470035986 0470035986 9780470035962 047003596X
OCLC Number: 180771236
Description: 1 online resource (x, 366 pages) : illustrations
Contents: Preface. 1. The need for more than one random-effect term when fitting a regression line. 2. The need for more than one random-effect term in a designed experiment. 3. Estimation of the variances of random-effect terms. 4. Interval estimates for fixed-effect terms in mixed models. 5. Estimation of random effects in mixed models: best linear unbiased predictors. 6. More advanced mixed models for more elaborate data sets. 7. Two case studies. 8. The use of mixed models for the analysis of unbalanced experimental designs. 9. Beyond mixed modelling. 10. Why is the criterion for fitting mixed models called residual maximum likelihood? References. Index.
Responsibility: N.W. Galwey.

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"This book would be useful for anyone who sues GenStat and/or R desiring an introduction to applied mixed modeling, and they should certainly have a look." (Technometrics, August 2008) "This book Read more...

 
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