Applied Multivariate Research: Design and Interpretationprovides full coverage of the wide range of multivariate topics in a conceptual rather than mathematical approach. The authors gear the text toward the needs, level of sophistication, and interest in multivariate methodology of students in applied programswho need to focus on design and interpretation rather than the intricacies of specific computations.
For me the comprehensive nature of the text is most important – even when I don’t cover topics in class students gain value by being able to read about cluster analysis or ROC analysis in enough detail that they can conduct their own analyses. Students appreciate the integration with SPSS. There is an appropriate balance of “practice” and background so that students learn what they need to know about the techniques but also learn how to implement and interpret the analysis.
The key strengths are its clearly written explanations of OLS regression and logistic regression as well as its treatment of path analysis.
The comprehensive nature of the topics presented and the numerous figures and charts.
Thomas J. Keil
Organization is excellent.
Glenn J. Hansen
Well written and accessible. I find the additional readings at the end of the chapters to be valuable and have tracked down several of the sources for my own personal use.
Xiaofen Deng Keating
My students think the book is well written and the language is easy for them to understand
Larry Meyers earned his doctorate in Experimental Psychology, and has been a Professor in the Psychology Department at California State University, Sacramento for a number of years. He supervises research students and teaches research design courses as well as history of psychology at both the undergraduate and graduate level. His areas of expertise include test development and validation.
Glenn Gamst is Professor and Chair of the Psychology Department at the University of La Verne, where he teaches the doctoral advanced statistics sequence. He received his Ph.D. from the University of Arkansas in experimental psychology. His research interests include the effects of multicultural variables on clinical outcome. Additional research interests focus conversation memory and discourse processing.
A.J. Guarino received his B.A. from the University of California, Berkeley and a Ph.D. from the University of Southern California in statistics and research methodologies from the Department of Educational Psychology. He is professor of biostatistics at Massachusetts General Hospital, Institute of Health Professions. He is the statistician on numerous NIH grants and reviewer on several research journals.
Preface PART I. FOUNDATIONS
1. An Introduction to Multivariate Design
2. Some Fundamental Research Design Concepts
3A. Data Screening
3B. Data Screening Using SPSS PART II. THE INDEPENDENT VARIABLE VARIATE
4A. Bivariate Correlation and Simple Linear Regression
4B. Bivariate Correlation and Simple Linear Regression Using SPSS
5A. Multiple Regression
5B. Multiple Regression Using SPSS
6A. Logistic Regression
6B. Logistic Regression Using SPSS
7A. Discriminant Function Analysis
7B. Two-Group Discriminant Function Analysis Using SPSS PART III. THE DEPENDENT VARIABLE VARIATE
8A. Univariate Comparisons of Means
8B. Univariate Comparisons of Means Using SPSS
9A. MANOVA: Comparing Two Groups
9B. Two-Group MANOVA Using SPSS
10A. MANOVA: Comparing Three or More Groups
10B. MANOVA: Comparing Three or More Groups Using SPSS
11A. MANOVA: Two-Way Factorial
11B. MANOVA: Two-Way Factorial Using SPSS PART IV. THE EMERGENT VARIATE
12A. Principle Components and Factor Analysis
12B. Principle Components and Factor Analysis Using SPSS
13A. Confirmatory Factor Analysis
13B. Confirmatory Factor Analysis Using AMOS PART V. MODEL FITTING
14A. Causal Modeling: Path Analysis and Structural Equation Modeling
14B. Path Analysis Using SPSS and AMOS
15A. Applying a Model to Different Groups
15B. Assessing Model Invariance Between Groups Using AMOS Appendix References Name Index Subject Index About the Authors