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Applied multivariate statistical concepts /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Applied multivariate statistical concepts /Debbie L. Hahs-Vaughn.
作者:	Hahs-Vaughn, Debbie L.,
出版者:	New York, NY :Routledge,2025.
面頁冊數:	xxiv, 850 p. :ill. ;27 cm.
標題:	Multivariate analysis
ISBN:	9781032276076 :

Applied multivariate statistical concepts /
Hahs-Vaughn, Debbie L.,

Applied multivariate statistical concepts /Debbie L. Hahs-Vaughn. - 2nd ed. - New York, NY :Routledge,2025. - xxiv, 850 p. :ill. ;27 cm.

Includes bibliographical references and index.

Multivariate Statistics -- Univariate and Bivariate Statistics Review -- Data Screening -- Multiple Linear Regression -- Logistic Regression -- Multivariate Analysis of Variance: Single Factor, Factorial, and Repeated Measures Designs -- Discriminant Analysis -- Cluster Analysis -- Exploratory Factor Analysis -- Path Analysis, Confirmatory Factor Analysis, and Structural Equation Modeling -- Multilevel Linear Modeling -- Propensity Score Analysis.

"This second edition of Applied Multivariate Statistical Concepts, covers the classic and cutting-edge multivariate techniques used in today's research. Through clear writing and engaging pedagogy and examples using real data, Hahs-Vaughn walks students through the most used methods to learn why and how to apply each technique. A conceptual approach with a higher than usual text-to-formula ratio helps reader's master key concepts so they can implement and interpret results generated by today's sophisticated software. Additional features include examples using real data from the social sciences; templates for writing research questions and results that provide manuscript-ready models; step-by-step instructions on using R and SPSS statistical software with screenshots and annotated output; clear coverage of assumptions including how to test them and the effects of their violation; and conceptual, computational, and interpretative example problems that mirror the real-world problems students encounter in their studies and careers. This edition features expanded coverage of topics such as propensity score analysis; path analysis and confirmatory factor analysis; centering, moderation effects, and power as related to multilevel modelling. New topics are introduced such as addressing missing data and latent class analysis, while each chapter features an introduction to using R statistical software. This textbook is ideal for courses on multivariate statistics/analysis/design, advanced statistics and quantitative techniques, as well as for graduate students broadly in social sciences, education and behavioral sciences. It also appeals to researchers with no training in multivariate methods"--

ISBN: 9781032276076 :NT$5365

LCCN: 2024029508Subjects--Topical Terms:

217219
Multivariate analysis

LC Class. No.: QA278 / .H336 2025

Dewey Class. No.: 519.5/35

Applied multivariate statistical concepts /
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245 1 0 $a Applied multivariate statistical concepts / $c Debbie L. Hahs-Vaughn.
250 $a 2nd ed.
260 $a New York, NY : $b Routledge, $c 2025.
300 $a xxiv, 850 p. : $b ill. ; $c 27 cm.
504 $a Includes bibliographical references and index.
505 0 $a Multivariate Statistics -- Univariate and Bivariate Statistics Review -- Data Screening -- Multiple Linear Regression -- Logistic Regression -- Multivariate Analysis of Variance: Single Factor, Factorial, and Repeated Measures Designs -- Discriminant Analysis -- Cluster Analysis -- Exploratory Factor Analysis -- Path Analysis, Confirmatory Factor Analysis, and Structural Equation Modeling -- Multilevel Linear Modeling -- Propensity Score Analysis.
520 $a "This second edition of Applied Multivariate Statistical Concepts, covers the classic and cutting-edge multivariate techniques used in today's research. Through clear writing and engaging pedagogy and examples using real data, Hahs-Vaughn walks students through the most used methods to learn why and how to apply each technique. A conceptual approach with a higher than usual text-to-formula ratio helps reader's master key concepts so they can implement and interpret results generated by today's sophisticated software. Additional features include examples using real data from the social sciences; templates for writing research questions and results that provide manuscript-ready models; step-by-step instructions on using R and SPSS statistical software with screenshots and annotated output; clear coverage of assumptions including how to test them and the effects of their violation; and conceptual, computational, and interpretative example problems that mirror the real-world problems students encounter in their studies and careers. This edition features expanded coverage of topics such as propensity score analysis; path analysis and confirmatory factor analysis; centering, moderation effects, and power as related to multilevel modelling. New topics are introduced such as addressing missing data and latent class analysis, while each chapter features an introduction to using R statistical software. This textbook is ideal for courses on multivariate statistics/analysis/design, advanced statistics and quantitative techniques, as well as for graduate students broadly in social sciences, education and behavioral sciences. It also appeals to researchers with no training in multivariate methods"-- $c Provided by publisher.
650 0 $a Multivariate analysis $3 217219
650 0 $a Mathematical statistics $3 182294