1st Edition
Understanding Multivariate Research A Primer For Beginning Social Scientists
216 Pages
by
Routledge
104 Pages
by
Routledge
104 Pages
by
Routledge
Also available as eBook on:
Although nearly all major social science departments offer graduate students training in quantitative methods, the typical sequencing of topics generally delays training in regression analysis and other multivariate techniques until a student's second year. William Berry and Mitchell Sanders's Understanding Multivariate Research fills this gap with a concise introduction to regression analysis and... Read more
* List of Tables and Figures * Preface for Teachers and Students * Acknowledgments Introduction * The Concept of Causation * Experimental Research * The Logic Underlying Regression Analysis * Some Necessary Math Background The Bivariate Regression Model * The Equation * The Intercept * The Slope Coefficient * The Error or Disturbance Term * Some Necessary Assumptions * Estimating Coefficients with Data from a Sample The Multivariate Regression Model * The Value of Multivariate Analysis * Interpreting the Coefficients of a Multivariate Regression Model * Dichotomous and Categorical Independent Variables * The Assumptions of Multivariate Regression * Choosing the Independent Variables for a Regression Model Evaluating Regression Results * Standardized Coefficients * Strong Relationships Among the Independent Variables: The Problem of Multicollinearity * Measuring the Fit of a Regression Model * Statistical Significance * Cross-Sectional vs. Time-Series Data Some Illustrations of Multiple Regression * Lobbying in Congress * Population Dynamics and Economic Development Advanced Topics * Interaction vs. Nonlinearity * Interactive Models * Nonlinear Models * Dichotomous Dependent Variables: Probit and Logit * Multi-equation Models: Simultaneous Equation Models and Recursive Causal Models Conclusion * Glossary * References * Index
Biography
William Berry
