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An R Companion for Applied Statistics II
Multivariable and Multivariate Techniques

- Danney Rasco - West Texas A&M University, USA

**Other Titles in:**

Quantitative Methods | Research Methods in Psychology | Statistical Computing Environments

November 2020 | 288 pages | SAGE Publications, Inc

**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.### Sample Materials & Chapters

CHAPTER 1 • Beyond Two Variables and Null Hypothesis...

CHAPTER 2 • Advanced Data Screening, Outliers...