Generalized, Linear, and Mixed Models, Vol. 1
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For graduate students and practicing statisticians, McCulloch (biostatistics, U. of California-San Francisco) and Searle (biometry, Cornell U.) begin by reviewing the basics of linear models and linear mixed models, in which the variance structure is based on random effects and their variance components. Then they head into the more difficult terrain of generalized linear models, generalized linear mixed models, and even some nonlinear models. The early chapters could provide a core for a one-quarter or one-semester course, or part of a course on linear models.
LF/534570557/R
Data sheet
- Name of the Author
- Charles E. McCulloch
Shayle R. Searle - Language
- English
- Series
- Wiley Series in Probability and Statistics
- ISBN
- 9780471193647
- Release date
- 2001
