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Applied Multivariate Research: Design and Interpretation 3ed

by Lawrence Meyers, Glenn Gamst and Anthony Guarino Sage Publications, Inc
Pub Date:
01/2017
ISBN:
9781506329765
Format:
Hbk 1016 pages
Price:
AU$280.00 NZ$283.48
Product Status: In Stock Now
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Instructors
& Academics:
Applied Multivariate Research: Design and Interpretation, Third Edition by Lawrence S. Meyers, Glenn Gamst, and A.J. Guarinoprovides full coverage of the wide range of multivariate topics that graduate students across the social and behavioral sciences encounter, using a conceptual, non-mathematical, approach.


 


Addressing correlation, multiple regression, exploratory factor analysis, MANOVA, path analysis, and structural equation modeling, it is geared toward the needs, level of sophistication, and interest in multivariate methodology that serves students in applied programs in the social and behavioral sciences. Readers are encouraged to focus on design and interpretation rather than the intricacies of specific computations.

Part I: An Introduction to Multivariate Design
Chapter 1: An Introduction to Multivariate Design
Chapter 2: Some Fundamental Research Design Concepts
Chapter 3A: Data Screening
Chapter 3B: Data Screening Using IBM SPSS
Part II: Basic and Advanced Regression Analysis
Chapter 4A: Bivariate Correlation and Simple Linear Regression
Chapter 4B: Bivariate Correlation and Simple Linear Regression Using IBM SPSS
Chapter 5A: Multiple Regression Analysis
Chapter 5B: Multiple Regression Analysis Using IBM SPSS
Chapter 6A: Beyond Statistical Regression
Chapter 6B: Beyond Statistical Regression Using IBM SPSS
Chapter 7A: Canonical Correlation Analysis
Chapter 7B: Canonical Correlation Analysis Using IBM SPSS
Chapter 8A: Multilevel Modeling
Chapter 8B: Multilevel Modeling Using IBM SPSS
Chapter 9A: Binary and Multinomial Logistic Regression and ROC Analysis
Chapter 9B: Binary and Multinomial Logistic Regression and ROC Analysis Using IBM SPSS
Part III: Structural Relationships of Measured and Latent Variables
Chapter 10A: Principal Components Analysis and Exploratory Factor Analysis
Chapter 10B: Principal Components Analysis and Exploratory Factor Analysis Using IBM SPSS
Chapter 11A: Confirmatory Factor Analysis
Chapter 11B: Confirmatory Factor Analysis Using IBM SPSS AMOS
Chapter 12A: Path Analysis: Multiple Regression Analysis
Chapter 12B: Path Analysis: Multiple Regression Analysis Using IBM SPSS
Chapter 13A: Path Analysis: Structural Equation Modeling
Chapter 13B: Path Analysis: Structural Equation Modeling Using IBM SPSS AMOS
Chapter 14A: Structural Equation Modeling
Chapter 14B: Structural Equation Modeling Using IBM SPSS AMOS
Chapter 15A: Measurement and Structural Equation Modeling Invariance: Applying a Model to Different Group
Chapter 15B: Assessing Measurement and Structural Invariance for Confirmatory Factor Analysis and Structural Equation Models Using IBM SPSS AMOS
Part IV: Consolidating Stimuli and Cases
Chapter 16A: Multidimensional Scaling
Chapter 16B: Multidimensional Scaling Using IBM SPSS
Chapter 17A: Cluster Analysis
Chapter 17B: Cluster Analysis Using IBM SPSS
Part V: Comparing Scores
Chapter 18A: Between Subjects Comparisons of Means
Chapter 18B: Between Subjects ANCOVA, MANOVA, and MANCOVA Using IBM SPSS
Chapter 19A: Discriminant Function Analysis
Chapter 19B: Three-Group Discriminant Function Analysis Using IBM SPSS
Chapter 20A: Survival Analysis
Chapter 20B: Survival Analysis Using IBM SPSS
References
Appendix A: Statistics Tables
Index

“A major strength of this text is that it covers the new features of the most recent SPSS® edition. With the step-by-step tutorial on the new features, students and empirical researchers can use it as a handbook when they conduct data analysis.” 
Lawrence S. Meyers - California State University, Sacramento     Glenn Gamst - University of La Verne     


A.J. Guarino - MGH Institute of Health Professions