Applied multivariate research : design and interpretation / Lawrence S. Meyers, Glenn Gamst and A. J. Guarino.
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- 9781412988117 (cloth)
- 000SA.07 23 M613
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000SA.07 K65 Principles and practice of structural equation modeling / | 000SA.07 K82 Introduction to multivariate analysis : | 000SA.07 M217 Simulating copulas : | 000SA.07 M613 Applied multivariate research : | 000SA.07 P339 Modeling and analysis of compositional data / | 000SA.07 P926 The statistical analysis of multivariate failure time data: a marginal modeling approach/ | 000SA.07 R888 Some aspects of multivariate analysis/ |
Includes bibliographical references (p. 1032-1055) and index.
Preface --
Author bios --
PART I: The basics of 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: Comprisons of Means
Chapter 4A: Univariate comparison of means --
Chapter 4B: Univariate comparison of means using IBM SPSS --
Chapter 5A: Multivariate analysis of variance --
Chapter 5B: Multivariate analysis of variance using IBM SPSS --
PART III: Predicting the value of a single variable
Chapter 6A: Bivariate correlation and simple linear regression --
Chapter 6B:Bivariate correlation and simple linear regression
using IBM SPSS --
Chapter 7A: Multiple regression : statistical methods --
Chapter 7B: Multiple regression : statistical methods using IBM SPSS --
Chapter 8A: Multiple regression : beyond statistical regression --
Chapter 8B: Multiple regression : beyond statistical regression using IBM SPSS --
Chapter 9A: Multilevel modeling --
Chapter 9B: Multilevel modeling using IBM SPSS --
Chapter 10A: Binary and multinomial logistic regression and roc characteristic analysis --
Chapter 10B: Binary and multinomial logistic regression and ROC analysis using IBM SPSS --
PART IV: Analysis of structure
Chapter 11A: Discriminant function analysis --
Chapter 11B: Discriminant function analysis using IBM SPSS --
Chapter 12A: Principal components analysis and exploratory factor analysis --
Chapter 12B: Principal components analysis and exploratory factor analysis using IBM SPSS--
Chapter 13A: Canonical correlation analysis--
Chapter 13B: Canonical correlation analysis using IBM SPSS--
Chapter 14A: Multidimensional scaling --
Chapter 14B: Multidimensional scaling using IBM SPSS--
Chapter 15A: Cluster analysis--
Chapter 15B: Cluster analysis using IBM SPSS --
PART V: Fitting models to data
Chapter 16A: Confirmatory factor analysis --
Chapter 16B: Confirmatory factor analysis using Amos --
Chapter 17A: Path analysis : multiple regression --
Chapter 17B: Path analysis : multiple regression using IBM SPSS--
Chapter 18A: Path analysis : structural modeling --
Chapter 18B: Path analysis: structural modeling using Amos--
Chapter 19A: Structural equation modeling--
Chapter 19B: Structural equation modeling using Amos--
Chapter 20A: Model invariance : applying a model to different groups--
Chapter 20B: Assessing model invariance using Amos--
References
Appendix A: Statistics Tables--
Appendix B: Selected IBM SPSS Amos menus and commands--
Author Index--
Subject Index--
Covering a wide range of multivariate topics, this book provides students in the social and behavioural sciences with a conceptual, non-mathematical approach.
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