Abstract
Part I: Foundations of Multiple Regression Analysis. Overview. Simple Linear Regression and Correlation. Regression Diagnostics. Computers and Computer Programs. Elements of Multiple Regression Analysis: Two Independent Variables. General Method of Multiple Regression Analysis: Matrix Operations. Statistical Control: Partial and Semi-Partial Correlation. Prediction. Part II: Multiple Regression Analysis. Variance Partitioning. Analysis of Effects. A Categorical Independent Variable: Dummy, Effect, And Orthogonal Coding. Multiple Categorical Independent Variables and Factorial Designs. Curvilinear Regression Analysis. Continuous and Categorical Independent Variables I: Attribute-Treatment Interaction, Comparing Regression Equations. Continuous and Categorical Independent Variables II: Analysis of Covariance. Elements of Multilevel Analysis. Categorical Dependent Variable: Logistic Regression. Part III: Structural Equation Models. Structural Equation Models with Observed Variables: Path Analysis. Structural Equation Models with Latent Variables. Part IV: Multivariate Analysis. Regression, Discriminant, And Multivariate Analysis of Variance: Two Groups. Canonical, Discriminant, And Multivariate Analysis of Variance: Extensions. Appendices.
Keywords
Related Publications
Basics of Structural Equation Modeling
PART ONE: BACKGROUND What Does It Mean to Model Hypothesized Causal Processes with Nonexperimental Data? History and Logic of Structural Equation Modeling PART TWO: BASIC APPROA...
Using multivariate statistics
In this Section: 1. Brief Table of Contents 2. Full Table of Contents 1. BRIEF TABLE OF CONTENTS Chapter 1 Introduction Chapter 2 A Guide to Statistical Techniques: Using the Bo...
Structural Equation Modeling: Foundations and Extensions
Preface to the Second Edition 1. Historical Foundations of Structural Equation Modeling for Continuous and Categorical Latent Variables 2. Path Analysis: Modeling Systems of Str...
Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences
Contents: Preface. Introduction. Bivariate Correlation and Regression. Multiple Regression/Correlation With Two or More Independent Variables. Data Visualization, Exploration, a...
Applied Regression Analysis and Other Multivariable Methods
1. CONCEPTS AND EXAMPLES OF RESEARCH. Concepts. Examples. Concluding Remarks. References. 2. CLASSIFICATION OF VARIABLES AND THE CHOICE OF ANALYSIS. Classification of Variables....
Publication Info
- Year
- 1982
- Type
- book
- Citations
- 3785
- Access
- Closed