Analysis of Multiple Dependent Variables

by Patrick Dattalo

Overview

Multivariate procedures allow social workers and other human services researchers to analyze complex, multidimensional social problems and interventions in ways that minimize oversimplification. This pocket guide provides a concise, practical, and economical introduction to four procedures for the analysis of multiple dependent variables: multivariate analysis of variance (MANOVA), multivariate analysis of covariance (MANCOVA), multivariate multiple regression (MMR), and structural equation modeling (SEM).

Each procedure will be presented in a way that allows readers to compare and contrast them in terms of (1) appropriate research context; (2) required statistical assumptions, including levels of measurement of variables to be modeled; (3) analytical steps; (4) sample size; and (5) strengths and weaknesses. This invaluable guide facilitates course extensibility in scope and depth by allowing instructors to supplement course content with rigorous statistical procedures. Detailed annotated examples using Stata, SPSS (PASW), SAS, and Amos, together with additional resources, discussion of key terms, and a companion website, make this an unintimidating guide for producers and consumers of social work research knowledge.

Product Details

ISBN-13:	9780199773596
Publisher:	Oxford University Press
Publication date:	02/11/2013
Series:	Pocket Guide to Social Work Research Methods
Edition description:	New Edition
Pages:	190
Product dimensions:	5.50(w) x 8.10(h) x 0.50(d)

About the Author

Patrick Dattalo, PhD, is Professor of Social Work at Virginia Commonwealth University.

Table of Contents

1. Basic Concepts and Assumptions
2. Multivariate Analysis of Variance
3. Multivariate Analysis of Covariance
4. Multivariate Multiple Regression
5. Structural Equation Modeling
6. Choosing among Procedures for the Analysis of Multiple Dependent Variables
References
Index