Applied multivariate research: design and interpretation

Using a conceptual, non-mathematical approach, the updated Third Edition provides full coverage of the wide range of multivariate topics that graduate students across the social and behavioral sciences encounter. Authors Lawrence S. Meyers, Glenn Gamst, and A.J. Guarino integrate innovative multicultural topics in examples throughout the book, which include both conceptual and practical coverage of : statistical techniques of data screening; multiple regression, multilevel modeling, exploratory factor analysis, discriminant analysis; structural equation modeling, structural equation modeling invariance, survival analysis, multidimensional scaling, and cluster analysis. [Sage Publ.].

Preface -- About the authors -- An introduction to multivariate design -- An introduction to multivariate design -- Some fundamental research design concepts -- Chapter 3A : data screening -- Chapter 3B : data screening using IBM SPSS -- 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 -- Structural relationships of measured and latent variables -- Chapter 10A : Principal components analysis and exploratory factor analysis -- Chapter 10B : principal components analysis and explora…