Cargando…
SAS for mixed models /
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 outsi...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , , , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cary, NC :
SAS Institute,
2007.
|
| Edición: | Second edition. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
| Sumario: | 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 scope is both broad and deep. Examples are included from numerous areas of application and range from introductory examples to technically advanced case studies. The book is intended to be useful to as diverse an audience as possible, although persons with some knowledge of analysis of variance and regression analysis will benefit most. |
|---|---|
| Descripción Física: | 1 online resource (828 pages) : illustrations |
| Bibliografía: | Includes bibliographical references, and index. |
| ISBN: | 9781599940786 1599940787 |