Regression analysis for social sciences / Alexander von Eye, Christof Schuster.

Format:

Book

Author/Creator:

Eye, Alexander von.

Contributor:

Schuster, Christof.

Language:

English

Subjects (All):

Social sciences--Statistical methods.

Social sciences.

Regression analysis.

Physical Description:

1 online resource (403 p.)

Place of Publication:

San Diego, Calif. : Academic Press, 1998.

Language Note:

English

Summary:

Regression Analysis for Social Sciences presents methods of regression analysis in an accessible way, with each method having illustrations and examples. A broad spectrum of methods are included: multiple categorical predictors, methods for curvilinear regression, and methods for symmetric regression. This book can be used for courses in regression analysis at the advanced undergraduate and beginning graduate level in the social and behavioral sciences. Most of the techniques are explained step-by-step enabling students and researchers to analyze their own data. Examples include data fr

Contents:

Front Cover; Regression Analysis for Social Sciences; Copyright Page; Contents; Preface; CHAPTER 1. INTRODUCTION; CHAPTER 2. SIMPLE LINEAR REGRESSION; 2.1 Linear Functions and Estimation; 2.2 Parameter Estimation; 2.3 Interpreting Regression Parameters; 2.4 Interpolation and Extrapolation; 2.5 Testing Regression Hypotheses; CHAPTER 3. MULTIPLE LINEAR REGRESSION; 3.1 Ordinary Least Squares Estimation; 3.2 Data Example; 3.3 Multiple Correlation and Determination; 3.4 Significance Testing; CHAPTER 4. CATEGORICAL PREDICTORS; 4.1 Dummy and Effect Coding; 4.2 More Than Two Categories

4.3 Multiple Categorical PredictorsCHAPTER 5. OUTLIER ANALYSIS; 5.1 Leverage Outliers; 5.2 Remedial Measures; CHAPTER 6. RESIDUAL ANALYSIS; 6.1 Illustrations of Residual Analysis; 6.2 Residuals and Variable Relationships; CHAPTER 7. POLYNOMIAL REGRESSION; 7.1 Basics; 7.2 Orthogonal Polynomials; 7.3 Example of Non-Equidistant Predictors; CHAPTER 8. MULTICOLLINEARITY; 8.1 Diagnosing Multicollinearity; 8.2 Countermeasures to Multicollinearity; CHAPTER 9. MULTIPLE CURVILINEAR REGRESSION; CHAPTER 10. INTERACTION TERMS IN REGRESSION; 10.1 Definition and Illustrations; 10.2 Multiplicative Terms

10.3 Variable CharacteristicsCHAPTER 11. ROBUST REGRESSION; 11.1 The Concept of Robustness; 11.2 Models of Robust Regression; 11.3 Computational Issues; CHAPTER 12. SYMMETRIC REGRESSION; 12.1 Pearson's Orthogonal Regression; 12.2 Other Solutions; 12.3 A General Model for OLS Regression; 12.4 Robust Symmetrical Regression; 12.5 Computational Issues; CHAPTER 13. VARIABLE SELECTION TECHNIQUES; 13.1 A Data Example; 13.2 Best Subset Regression; 13.3 Stepwise Regression; 13.4 Discussion; CHAPTER 14. REGRESSION FOR LONGITUDINAL DATA; 14.1 Within Subject Correlation

14.2 Robust Modeling of Longitudinal Data14.3 A Data Example; CHAPTER 15. PIECEWISE REGRESSION; 15.1 Continuous Piecewise Regression; 15.2 Discontinuous Piecewise Regression; CHAPTER 16. DICHOTOMOUS CRITERION VARIABLES; CHAPTER 17. COMPUTATIONAL ISSUES; 17.1 Creating a SYSTAT System File; 17.2 Simple Regression; 17.3 Curvilinear Regression; 17.4 Multiple Regression; 17.5 Regression Interaction; 17.6 Regression with Categorical Predictors; 17.7 The Partial Interaction Strategy; 17.8 Residual Analysis; 17.9 Missing Data Estimation; 17.10 Piecewise Regression

APPENDIX A. ELEMENTS OF MATRIX ALGEBRAA.1 Definition of a Matrix; A.2 Types of Matrices; A.3 Transposing Matrices; A.4 Adding Matrices; A.5 Multiplying Matrices; A.6 The Rank of a Matrix; A.7 The Inverse of a Matrix; A.8 The Determinant of a Matrix; A.9 Rules for Operations with Matrices; A.10 Exercises; APPENDIX B. BASICS OF DIFFERENTIATION; APPENDIX C. BASICS OF VECTOR DIFFERENTIATION; APPENDIX D. POLYNOMIALS; D.1 Systems of Orthogonal Polynomials; D.2 Smoothing Series of Measures; APPENDIX E. DATA SETS; E.1 Recall Performance Data; E.2 Examination and State Anxiety Data; References; Index

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

ISBN:

1-281-05712-6

9786611057121

0-08-055082-7

OCLC:

476098217