| Description |
xiv, 1058 pages : illustrations ; 25 cm |
| Contents |
Part 1. Foundations of multiple regression analysis. Ch. 1 Overview -- Ch. 2 Simple linear regression and correlation -- Ch. 3 Regression Diagnostics -- Ch. 4 Computers and computer programs -- Ch. 5 Elements of multiple regression analysis:Two independent variables -- Ch. 6 General method of multiple regressiion analysis:Matrix operations -- Ch. 7 Statistical control:Partial and semipartial correlation -- Ch. 8 Prediction. Part 2 Multiple Regression Analysis:Explanation. Ch. 9 Variance partitioning -- Ch. 10 Analysis of effects -- Ch. 11 A categorical independent variable:dummy, effect and orthogonal coding -- Ch. 12 Multiple categorical independent variables and factorial designs -- Ch. 13 Curvilinear regression analysis -- Ch. 14 Continuous and categorical independent variables - 1:Attribute-treatment interaction; comparing regression equations -- Ch. 15 Continuous and categorical independent variables-11:Ananysis of covariance -- Ch. 16 Elements of multilevel analysis -- Ch. 17 Categorical dependent variable:logistic regression. Part 3 Structural Equation Models. Ch. 18 Structural equation models with observed variables:Path analysis -- Ch. 19 Structural equation models with latent variables. Part 4 Multivariate Analysis. Ch. 20 Regression and discriminant analysis -- Ch. 21 Canonical and discriminant analysis, and multivariate analysis of variance. Appendix A: Matrix Algebra: an introduction. Appendix B: Tables |
| Bibliography |
Includes bibliographical references (pages 1002-1033) and index |
| Subject |
Psychology -- Research.
|
|
Regression analysis.
|
| LC no. |
96078486 |
| ISBN |
0030728312 |
|
