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Informationen zum Autor Lawrence S. 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 levels. 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. His research interests include the effects of multicultural variables on clinical outcome. Additional research interests focus on conversation memory and discourse processing. He received his PhD in experimental psychology from the University of Arkansas . A. J. Guarino is a professor of biostatistics at Massachusetts General Hospital, Institute of Health Professions. He is the statistician on numerous National Institutes of Health grants and a reviewer on several research journals. He received his BA from the University of California, Berkeley, and a PhD in statistics and research methodologies from the Department of Educational Psychology, the University of Southern California . Klappentext Using a conceptual, non-mathematical approach, the updated Third Edition of Applied Multivariate Research: Design and Interpretation 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. Zusammenfassung Provides 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. Inhaltsverzeichnis Preface About the Authors PART I: FUNDAMENTALS OF MULTIVARIATE DESIGN Chapter 1: An Introduction to Multivariate Design 1.1 The Use of Multivariate Designs 1.2 The Definition of the Multivariate Domain 1.3 The Importance of Multivariate Designs 1.4 The General Form of a Variate 1.5 The Type of Variables Combined to Form a Variate 1.6 The General Organization of the Book Chapter 2: Some Fundamental Research Design Concepts 2.1 Populations and Samples 2.2 Variables and Scales of Measurement 2.3 Independent Variables, Dependent Variables, and Covariates 2.4 Between Subjects and Within Subjects Independent Variables 2.5 Latent Variables and Measured Variables 2.6 Endogenous and Exogenous Variables 2.7 Statistical Significance 2.8 Statistical Power 2.9 Recommended Readings Chapter 3A: Data Screening 3A.1 Overview 3A.2 Value Cleaning 3A.3 Patterns of Missing Values 3A.4 Overview of Methods of Handling Missing Data 3A.5 Deletion Methods of Handling Missing Data 3A.6 Single Imputation Methods of Handling Missing Data 3A.7 Modern Imputation Methods of Handling Missing Data 3A.8 Recommendations for Handling Missing Data 3A.9 Outliers 3A.10 Using Descriptive Statistics in Data Screening 3A.11 Using Pictorial Representations in Data Screening 3A.12 Multivariate Statistical Assumptions Underlying the General Linear Model 3A.13 Data Transformations 3A.14 Recommended Readings Chapter 3B: Data Screenin...
