ANOVA and Mixed Models: A Short Introduction Using R provides both
the practitioner and researcher a compact introduction to the analysis
of data from the most popular experimental designs. Based on knowledge
from an introductory course on probability and statistics, the
theoretical foundations of the most important models are introduced. The
focus is on an intuitive understanding of the theory, common pitfalls in
practice, and the application of the methods in R. From data
visualization and model fitting, up to the interpretation of the
corresponding output, the whole workflow is presented using R. The book
does not only cover standard ANOVA models, but also models for more
advanced designs and mixed models, which are common in many practical
applications.
Features
-
Accessible to readers with a basic background in probability and
statistics
-
Covers fundamental concepts of experimental design and cause-effect
relationships
-
Introduces classical ANOVA models, including contrasts and multiple
testing
-
Provides an example-based introduction to mixed models
-
Features basic concepts of split-plot and incomplete block designs
-
R code available for all steps
-
Supplementary website with additional resources and updates available
at https: //stat.ethz.ch/ meier/teaching/book-anova/
This book ** is primarily aimed at students, researchers, and
practitioners from all areas who wish to analyze corresponding data with
R. Readers will learn a broad array of models hand-in-hand with R,
including the applications of some of the most important add-on
packages.**
