Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences

Table of contents

• Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences i
• Title Page iii
• Contents vii
• Preface xxv
• Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences xxix
• 1: Introduction 1
• 2: Bivariate Correlation and Regression 19
• 3: Multiple Regression/ Correlation with Two or More Independent Variables 64
• 4: Data Visualization, Exploration, and Assumption Checking: Diagnosing and Solving Regression Problems I 101
• 5: Data-Analytic Strategies Using Multiple Regression/Correlation 151
• 6: Quantitative Scales, Curvilinear Relationships, and Transformations 193
• 7: Interactions Among Continuous Variables 255
• 8: Categorical or Nominal Independent Variables 302
• 9: Interactions with Categorical Variables 354
• 10: Outliers and Multicollinearity: Diagnosing and Solving Regression Problems II 390
• 11: Missing Data 431
• 12: Multiple Regression/ Correlation and Causal Models 452
• 13: Alternative Regression Models: Logistic, Poisson Regression, and the Generalized Linear Model 479
• 14: Random Coefficient Regression and Multilevel Models 536
• 15: Longitudinal Regression Methods 568
• 16: Multiple Dependent Variables: Set Correlation 608
• Appendices 629
• Appendix 1 - The Mathematicalbasisfor Multiple Regression/Correlation and Identification of the Inverse Matrix Elements 631
• Appendix 2 - Determination of the Inverse Matrix and Applications Thereof 636
• Appendix Tables 643
• References 655
• Glossary 671
• Statistical Symbols and Abbreviations 683
• Author Index 687
• Subject Index 691

Work saved from this book