Tell your friends about this item:
Linear Mixed-Effects Models Using R: A Step-by-Step Approach - Springer Texts in Statistics Andrzej Galecki 2013 edition
Linear Mixed-Effects Models Using R: A Step-by-Step Approach - Springer Texts in Statistics
Andrzej Galecki
Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. It is built up incrementally, starting with a summary of the concepts underlying simpler classes of linear models like the classical regression model, and carrying them forward to LMMs.
542 pages, 64 black & white illustrations, 47 black & white tables, biography
| Media | Books Hardcover Book (Book with hard spine and cover) |
| Released | February 5, 2013 |
| ISBN13 | 9781461438991 |
| Publishers | Springer-Verlag New York Inc. |
| Pages | 542 |
| Dimensions | 160 × 234 × 37 mm · 975 g |
| Language | English |