Danney Rasco (West Texas A & USA M University)

An R Companion for Applied Statistics II

Multivariable and Multivariate Techniques

• Broschiertes Buch

Produktbeschreibung

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 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.

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Produktdetails

• Verlag: SAGE Publications Inc
• Seitenzahl: 288
• Erscheinungstermin: 17. November 2020
• Englisch
• Abmessung: 189mm x 233mm x 14mm
• Gewicht: 488g
• ISBN-13: 9781071815571
• ISBN-10: 1071815571
• Artikelnr.: 59259999

Autorenporträt

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.

Inhaltsangabe

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