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An R Companion for Applied Statistics II
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An R Companion for Applied Statistics II
Multivariable and Multivariate Techniques

July 2020 | 288 pages | SAGE Publications, Inc
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An R Companion for Applied Statistics II: Multivariable and Multivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use R to analyze multivariate data. The book focuses on the statistics generally covered in an intermediate or multivariate statistics course and provides one or two ways to run each analysis in R. The book has been designed to be an R companion to Rebecca M. Warner's Applied Statistics II: Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide for a multivariate statistics course, without reference to the Warner text. Datasets and scripts to run the examples are provided on an accompanying website.
 
Preface
 
Acknowledgments
 
About the Author
 
CHAPTER 1 • Beyond Two Variables and Null Hypothesis Significance Testing
Confidence Intervals

 
Effect Size

 
Meta-Analysis

 
Chapter 1: Summary of Key Functions (AKA: Function Cheat Sheet)

 
 
CHAPTER 2 • Advanced Data Screening, Outliers, and Missing Values
Data Management

 
Coding Missing Values

 
Screening Data

 
Chapter 2: Summary of Key Functions (AKA: Function Cheat Sheet)

 
 
CHAPTER 3 • Statistical Control
Including a Third Variable in Graphs

 
Including a Third Variable Quantitatively

 
Chapter 3: Summary of Key Functions (AKA: Function Cheat Sheet)

 
Appendix 3: R Instructions to Accompany Warner (2020b)

 
 
CHAPTER 4 • Statistical Control With Regression Analysis
Visualizing Associations Between Three Variables

 
Performing Regressions and Semipartial Correlations

 
Chapter 4: Summary of Key Functions (AKA: Function Cheat Sheet)

 
Appendix 4: R Instructions to Accompany Warner (2020b)

 
 
CHAPTER 5 • Beyond Three Variables: Regression With Multiple Predictors
Standard Regression

 
User-Determined Regression

 
Data-Driven Regression

 
Chapter 5: Summary of Key Functions (AKA: Function Cheat Sheet)

 
Appendix 5: R Instructions to Accompany Warner (2020b)

 
 
CHAPTER 6 • Regression With Dummy Variables
One-Way Between-Subjects Analysis of Variance (ANOVA)

 
Regression With Dummy Variables

 
Regression With Quantitative and Dummy Variables

 
Chapter 6: Summary of Key Functions (AKA: Function Cheat Sheet)

 
Appendix 6: R Instructions to Accompany Warner (2020b)

 
 
CHAPTER 7 • Moderation
Interactions With Categorical Predictors

 
Interactions With a Categorical and Quantitative Predictor

 
Interactions With Two Quantitative Predictors

 
Interactions with a Categorical and Quantitative Predictor

 
Interactions with Two Quantitative Predictors

 
Chapter 7: Summary of Key Functions (AKA: Function Cheat Sheet)

 
Appendix 7: R Instructions to Accompany Warner (2020b)

 
 
CHAPTER 8 • Analysis of Covariance
Checking Assumptions

 
Performing ANCOVA

 
Presenting Results

 
Chapter 8: Summary of Key Functions (AKA: Function Cheat Sheet)

 
Appendix 8: R Instructions to Accompany Warner (2020b)

 
 
CHAPTER 9 • Mediation
Checking Assumptions

 
Performing Mediation Analysis

 
Presenting Results

 
Chapter 9: Summary of Key Functions (AKA: Function Cheat Sheet)

 
Appendix 9: R Instructions to Accompany Warner (2020b)

 
 
CHAPTER 10 • Discriminant Analysis
Checking Assumptions

 
Performing Discriminant Analysis

 
Presenting Results

 
Chapter 10: Summary of Key Functions (AKA: Function Cheat Sheet)

 
Appendix 10: R Instructions to Accompany Warner (2020b)

 
 
CHAPTER 11 • Multivariate Analysis of Variance
Checking Assumptions

 
Performing Multivariate Analysis of Variance

 
Performing Factorial Multivariate Analysis of Variance

 
Chapter 11: Summary of Key Functions (AKA: Function Cheat Sheet)

 
Appendix 11: R Instructions to Accompany Warner (2020b)

 
 
CHAPTER 12 • Exploratory Factor Analysis
Performing Principal Components Analysis

 
Performing Principal Axis Factor Analysis

 
Chapter 12: Summary of Key Functions (AKA: Function Cheat Sheet)

 
Appendix 12: R Instructions to Accompany Warner (2020b)

 
 
CHAPTER 13 • Reliability and Validity for Multiple-Item Scales
Test-Retest Reliability

 
Factor Analysis

 
Internal Reliability and Creating Scale Scores

 
Chapter 13: Summary of Key Functions (AKA: Function Cheat Sheet)

 
Appendix 13: R Instructions to Accompany Warner (2020b)

 
 
CHAPTER 14 • Repeated-Measures Tests: Further Exploration
Checking Assumptions

 
One-Way Repeated-Measures Analysis of Variance

 
Mixed Analysis of Variance

 
Chapter 14: Summary of Key Functions (AKA: Function Cheat Sheet)

 
Appendix 14: R Instructions to Accompany Warner (2020b)

 
 
CHAPTER 15 • Brief Introduction to Latent-Variable Structural Equation Modeling
Measurement Models

 
Mediation With Latent-Variable Structural Equation Modeling

 
Chapter 15: Summary of Key Functions (AKA: Function Cheat Sheet)

 
Appendix 15: R Instructions to Accompany Warner (2020b)

 
 
CHAPTER 16 • Binary Logistic Regression
Getting Familiar With the Data

 
Binary Logistic Regression

 
Presenting Results

 
Chapter 16: Summary of Key Functions (AKA: Function Cheat Sheet)

 
Appendix 16: R Instructions to Accompany Warner (2020b)

 
 
CHAPTER 17 • Additional Statistical Techniques
Dealing With Time

 
Dealing With Odd Distributions

 
Dealing With Interdependence

 
Concluding Thoughts

 
 
References

Supplements

Student Study Site
Open-access Student Resources include R code and data sets provided by the author for student download for completing in-chapter exercises.

Bundles