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Produktbild: Multiple Regression and Beyond

Multiple Regression and Beyond An Introduction to Multiple Regression and Structural Equation Modeling

Fr. 129.00

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

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.

Beschreibung

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.

Produktdetails

Einband

Taschenbuch
Erscheinungsdatum

30.09.2025
Abbildungen

430 SW-Abb., 430 SW-Zeichn., 66 Tabellen
Verlag Taylor & Francis

Produktdetails

Einband

Taschenbuch
Erscheinungsdatum

30.09.2025
Abbildungen

430 SW-Abb., 430 SW-Zeichn., 66 Tabellen
Verlag Taylor & Francis
Seitenzahl

712
Maße (L/B/H)

25.4/17.8/3.8 cm
Gewicht

1315 g
Auflage

4. Auflage
Sprache

Englisch
ISBN

978-1-03-252097-1
EU-Ansprechpartner

Taylor & Francis Verlag GmbH
Kaufingerstraße 24
80331 München
DE
GPSR@taylorandfrancis.com
Herstelleradresse

Taylor & Francis Group
5 Howick Place
SW1P 1WG London
UK
GPSR@taylorandfrancis.com

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  • Produktbild: Multiple Regression and Beyond

  • Preface
    Notes for the Fourth Edition
    Acknowledgments

    Part I: Multiple Regression
    Chapter 1: Simple bivariate regression
    Chapter 2: Multiple regression: Introduction
    Chapter 3: Multiple regression: More detail
    Chapter 4: Three and more independent variables and related issues
    Chapter 5: Three Types of multiple regression
    Chapter 6: Analysis of categorical variables
    Chapter 7: Regression with categorical and continuous variables
    Chapter 8: Testing for interactions and curves with continuous variables
    Chapter 9: Mediation, moderation, common cause, and suppression
    Chapter 10: Multiple regression: Summary, assumptions, diagnostics, power, and problems
    Chapter 11: Related methods: Quantile regression, logistic regression and multilevel modeling
    Part II: Beyond Multiple Regression: Structural Equation Modeling
    Chapter 12: Path modeling: Structural equation modeling with measured variables
    Chapter 13: Path analysis: Assumptions and dangers
    Chapter 14: Analyzing path models using SEM programs
    Chapter 15: Error: The scourge of research
    Chapter 16: Confirmatory factor analysis I
    Chapter 17: Putting it all together: Introduction to latent variable SEM
    Information Classification: General
    Chapter 18: Latent variable models II: Single indicators, correlated errors, multigroup models, panel models, dangers & assumptions
    Chapter 19: Latent means in SEM
    Chapter 20: Confirmatory factor analysis II: Invariance and latent means
    Chapter 21: Latent growth models
    Chapter 22: Latent variable interactions and multilevel modeling in SEM
    Chapter 23: Summary: Path analysis, CFA, SEM, mean structures, and latent growth models
    Appendices
    Appendix A: Data files and statistical program notes
    Appendices B: Review of basic statistics concepts
    Appendix C: Partial and semipartial correlation
    Appendix D: Symbols used in this book
    Appendix E: Useful formulae

    Reference
    Author index
    Subject index