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" Multiple regression and beyond : "
Timothy Z. Keith.
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BL
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| Record Number
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841222
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| Main Entry
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Keith, Timothy Z.,1952-
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| Title & Author
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Multiple regression and beyond : : an introduction to multiple regression and structural equation modeling /\ Timothy Z. Keith.
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| Edition Statement
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Third edition.
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| Publication Statement
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New York, NY :: Routledge,, 2019.
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| Page. NO
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1 online resource (xiii, 639 pages)
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| ISBN
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1315162342
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: 1351667912
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: 1351667920
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: 1351667939
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: 9781315162348
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: 9781351667913
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: 9781351667920
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: 9781351667937
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9781138061422
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9781138061446
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| Bibliographies/Indexes
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Includes bibliographical references and indexes.
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| Contents
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Multiple regression -- Simple bivariate regression -- Multiple regression : introduction -- Multiple regression : more detail -- Three and more independent variables and related issues -- Three types of multiple regression -- Analysis of categorical variables -- Regression with categorical and continuous variables -- Testing for interactions and curves with continuous variables -- Mediation, moderation, and common cause -- Multiple regression: summary, assumptions, diagnostics, power, and problems -- Related methods : logistic regression and multilevel modeling -- Beyond multiple regression : structural equation modeling -- Path modeling : structural equation modeling with measured variables -- Path analysis : assumptions and dangers -- Analyzing path models using sem programs -- Error: the scourge of research -- Confirmatory factor analysis I: -- Putting it all together: introduction to latent variable sem -- Latent variable models II: multigroup models, panel models, dangers & assumptions -- Latent means in SEM -- Confirmatory factor analysis II: invariance and latent means -- Latent growth models -- Latent variable interactions and multilevel models in SEM -- Summary: path analysis, cfa, sem, mean structures, and latent growth models -- Appendices.
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| Abstract
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Companion Website materials: https://tzkeith.com/ Multiple Regression and Beyond offers a conceptually-oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. This book:Covers both MR and SEM, while explaining their relevance to one anotherIncludes path analysis, confirmatory factor analysis, and latent growth modelingMakes extensive use of real-world research examples in the chapters and in the end-of-chapter exercisesExtensive use of figures and tables providing examples and illustrating key concepts and techniques New to this edition:New chapter on mediation, moderation, and common causeNew chapter on the analysis of interactions with latent variables and multilevel SEMExpanded coverage of advanced SEM techniques in chapters 18 through 22International case studies and examplesUpdated instructor and student online resources
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| Subject
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Regression analysis.
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EDUCATION-- Research.
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MATHEMATICS-- Applied.
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MATHEMATICS-- Probability Statistics-- General.
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Regression analysis.
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| Dewey Classification
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519.5/36
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| LC Classification
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HA31.3.K45 2019
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