SAS for Mixed Models, Second Edition | 
 enlarge | Author: Ramon C. Littell; George A. Milliken; Walter W. Stroup; Russell D. Wolfinger; Oliver; Ph.d. Schabenberber
Publisher: SAS Publishing
Category: Book
List Price: $89.95
Buy New: $71.97
You Save: $17.98 (20%)
New (13) Used (7) from $64.77
Avg. Customer Rating:  3 reviews
Sales Rank: 108052
Media: Paperback
Edition: 2nd
Number Of Items: 1
Pages: 840
Shipping Weight (lbs): 3.5
Dimensions (in): 10.9 x 8.3 x 1.3
ISBN: 1590475003
Dewey Decimal Number: 005.55
EAN: 9781590475003
ASIN: 1590475003
Publication Date: February 21, 2006
Availability: Usually ships in 24 hours
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| Editorial Reviews:
Product Description
The indispensable, up-to-date guide to mixed models using SAS. Discover the latest capabilities available for a variety of applications featuring the MIXED, GLIMMIX, and NLMIXED procedures in this valuable edition of the comprehensive mixed models guide for data analysis, completely revised and updated for SAS9. The theory underlying the models, the forms of the models for various applications, and a wealth of examples from different fields of study are integrated in the discussions of these models:
random effect only and random coefficients models
split-plot, multilocation, and repeated measures models
hierarchical models with nested random effects
analysis of covariance models
spatial correlation models
generalized linear mixed models
nonlinear mixed models
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| Customer Reviews:
 review December 23, 2007
2 out of 3 found this review helpful
Positive: 1.Well written in a field with limited sources.
Negative: 2. Not enough explanations for a lot of procedures.
2. Expensive
 good September 26, 2007
0 out of 3 found this review helpful
A pretty good book which is very suitable for some people who needs to use the mixed model. The content of this version is better than the previous version. I recommend this book.
A neccesary book for mixed model analysis May 18, 2007
I am a Ph.D. student, and I work with longitudinal and hierarchical data. I bought this book recently and I have only had a look at it. I like it very much. This book presents mixed model methodology in the setting of numerous applications and many examples are included from several applications areas. It is a useful book even to people with no muck knowledge of analysis of variance an regression analysis. You do not need to read the book from cover to cover. This book is certainly applied.
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