ANOVA and Mixed Models

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A01=Lukas Meier
advanced experimental design in R
analysis of variance
ANOVA Model
ANOVA Table
Author_Lukas Meier
BIBD
Block Factor
Category=GPS
Category=KCH
Category=PBT
causal inference
Chocolate Type
Confidence Interval
Data Set
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
experimental methodology
Experimental Units
Factorial Treatment Structure
Friedman Rank Sum Test
FWER
Group Ctrl
IBD
Interaction Plot
Latin Square Design
mixed effects
multiple testing
nonparametric statistics
Package Multcomp
power
random effects analysis
RCBD
research data interpretation
Row Column Designs
Seatbelt Sign
Simultaneous Confidence Intervals
Split Plot Designs
Split Plot Factor
statistical modelling
statistical power calculation
Strawberry Variety
Subplot Level
Tukey HSD

Product details

  • ISBN 9780367704223
  • Weight: 660g
  • Dimensions: 156 x 234mm
  • Publication Date: 04 Nov 2022
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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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 are available here.

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.

Lukas Meier is a senior scientist at the Seminar für Statistik at ETH Zürich. His main interests are teaching statistics at various levels, the application of statistics in many fields of applications using advanced ANOVA or regression models, and high-dimensional statistics. He co-leads the statistical consulting service at ETH Zürich and is the director of a continuing education program in applied statistics.

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