An R Companion for Applied Statistics II
Multivariable and Multivariate Techniques
1st Edition
Published on 17. November 2020
Book
Paperback/Softback
288 pages
978-1-0718-1557-1 (ISBN)
Description
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.
More details
Language
English
Place of publication
Thousand Oaks
United States
Target group
College/higher education
Dimensions
Height: 189 mm
Width: 233 mm
Thickness: 14 mm
Weight
488 gr
ISBN-13
978-1-0718-1557-1 (9781071815571)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Person
Danney Rasco is an Assistant Professor in the Department of Psychology, Sociology, and Social Work at West Texas A&M University. As a self-professed stats nerd, he enjoys (yes, enjoys) teaching three or four sections of statistics each year and simply smiles and shrugs when students shake their heads at his enthusiasm and zeal for data and the beautiful sport of number crunching. In his "free" time, he plans statistics workshops because he is a glutton for punishment. This love for statistics and teaching (i.e., nerdiness) resulted in a Summer Teaching Assistant Fellowship from the University of New Hampshire, an Intellectual Contribution Award from the College of Education and Social Sciences at West Texas A&M University. Dr. Rasco has a master's degree in clinical and counseling psychology from Midwestern State University, a master's degree and PhD in social psychology from the University of New Hampshire, and a Cognate in College Teaching from the University of New Hampshire. One day he will buy frames, perhaps with the proceeds from this book, and display these degrees proudly on a wall.
Content
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
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