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Applied multivariate research : design and interpretation / Lawrence S. Meyers, Glenn Gamst and A. J. Guarino.

By: Contributor(s): Material type: TextTextPublication details: Los Angeles : SAGE, c2013.Edition: 2nd edDescription: xx, 1078 p. ; 24 cmISBN:
  • 9781412988117 (cloth)
Subject(s): DDC classification:
  • 000SA.07 23 M613
Contents:
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--
Summary: 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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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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