Applied Multivariate Research

Design and Interpretation

Nonfiction, Social & Cultural Studies, Social Science, Statistics, Reference & Language, Reference, Research
Cover of the book Applied Multivariate Research by Lawrence S. Meyers, Glenn C. Gamst, Anthony J. Guarino, SAGE Publications
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Author: Lawrence S. Meyers, Glenn C. Gamst, Anthony J. Guarino ISBN: 9781506329789
Publisher: SAGE Publications Publication: October 28, 2016
Imprint: SAGE Publications, Inc Language: English
Author: Lawrence S. Meyers, Glenn C. Gamst, Anthony J. Guarino
ISBN: 9781506329789
Publisher: SAGE Publications
Publication: October 28, 2016
Imprint: SAGE Publications, Inc
Language: English

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. 

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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. 

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