Regression analysis for social sciences /
Eye, Alexander von
Regression analysis for social sciences / Alexander von Eye, Christof Schuster. - xv, 386 pages : illustrations ; 24 cm
Includes bibliographical references (pages 373-380) and index.
Introduction -- Simple Linear Regression -- Multiple Linear Regression -- Categorical Predictors -- Outlier Analysis -- Residual Analysis -- Polynomial Regression -- Multicollinearity -- Multiple Curvilinear Regression -- Interaction Terms in Regression -- Robust Regression -- Symmetric Regression -- Variable Selection Techniques -- Regression for Longitudinal Data -- Piecewise Regression -- Dichotomous Criterion Variables -- Computational Issues -- Elements of Matrix Algebra -- Basics of Differentiation -- Basics of Vector Differentiation -- Polynomials -- Data Sets.
"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 from the social and behavioral sciences as well as biology, making the book useful for readers with biological and biometrical backgrounds. Sample command and result files for SYSTAT are included in the text.Key Features* Presents accessible methods of regression analysis* Includes a broad spectrum of methods* Techniques are explained step-by-step* Provides sample command and result files for SYSTAT"--Publisher description.
0127249559 9780127249551
98084465
Social sciences--Statistical methods.
Regression analysis.
HA31.3 / .E94 1998
300.15195
Regression analysis for social sciences / Alexander von Eye, Christof Schuster. - xv, 386 pages : illustrations ; 24 cm
Includes bibliographical references (pages 373-380) and index.
Introduction -- Simple Linear Regression -- Multiple Linear Regression -- Categorical Predictors -- Outlier Analysis -- Residual Analysis -- Polynomial Regression -- Multicollinearity -- Multiple Curvilinear Regression -- Interaction Terms in Regression -- Robust Regression -- Symmetric Regression -- Variable Selection Techniques -- Regression for Longitudinal Data -- Piecewise Regression -- Dichotomous Criterion Variables -- Computational Issues -- Elements of Matrix Algebra -- Basics of Differentiation -- Basics of Vector Differentiation -- Polynomials -- Data Sets.
"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 from the social and behavioral sciences as well as biology, making the book useful for readers with biological and biometrical backgrounds. Sample command and result files for SYSTAT are included in the text.Key Features* Presents accessible methods of regression analysis* Includes a broad spectrum of methods* Techniques are explained step-by-step* Provides sample command and result files for SYSTAT"--Publisher description.
0127249559 9780127249551
98084465
Social sciences--Statistical methods.
Regression analysis.
HA31.3 / .E94 1998
300.15195