Preface
The subject of mixed linear models is taught in graduate-level statistics courses and is familiar to most statisticians. During the past 10 years, use of mixed model methodology has expanded to nearly all areas of statistical applications. It is routinely taught and applied even in disciplines outside traditional statistics. Nonetheless, many persons who are engaged in analyzing mixed model data have questions about the appropriate implementation of the methodology. Also, even users who studied the topic 10 years ago may not be aware of the tremendous new capabilities available for applications of mixed models.
Like the first edition, this second edition presents mixed model methodology in a setting that is driven by applications. The ...
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