Multiple Regression and Beyond
An Introduction to Multiple Regression and Structural Equation Modeling
2nd Edition
Published on 22. December 2014
Book
Hardback
600 pages
978-1-138-81194-2 (ISBN)
Description
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.
Covers both MR and SEM, while explaining their relevance to one another
Also includes path analysis, confirmatory factor analysis, and latent growth modeling
Figures and tables throughout provide examples and illustrate key concepts and techniques
For additional resources, please visit: http://tzkeith.com/
Covers both MR and SEM, while explaining their relevance to one another
Also includes path analysis, confirmatory factor analysis, and latent growth modeling
Figures and tables throughout provide examples and illustrate key concepts and techniques
For additional resources, please visit: http://tzkeith.com/
Reviews / Votes
I have had the opportunity to read quite a few books on quantitative methods in education during both my graduate work and more recently as an early career researcher, and this book occupies a singular and positive place among these.Todd M. Milford, University of Victoria
More details
Edition
2nd New edition
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Edition type
New edition
Illustrations
26 s/w Tabellen
Women, Science, and Technology; 26 Tables, black and white
Dimensions
Height: 254 mm
Width: 178 mm
Weight
1153 gr
ISBN-13
978-1-138-81194-2 (9781138811942)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Timothy Z. Keith
Multiple Regression and Beyond
An Introduction to Multiple Regression and Structural Equation Modeling
Book
01/2019
3rd Edition
Routledge
€294.50
Shipment within 10-20 days
Additional editions
Timothy Z. Keith
Multiple Regression and Beyond
An Introduction to Multiple Regression and Structural Equation Modeling
Book
12/2014
2nd Edition
Routledge
€102.93
Article exhausted; check for reprint
Person
Timothy Keith is Professor of Educational Psychology and Program Director of School Psychology at the University of Texas, Austin.
Content
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. Chapter 5: Three Types of MR. Chapter 6: Analysis of categorical variables. Chapter 7: Categorical & continuous variables. Chapter 8: Continuous variables: Interactions & curves. Chapter 9: Multiple regression: Summary, further study, and problems. Chapter 10: Related methods: Logistic regression and multilevel modeling. Part II: Beyond Multiple Regression: Structural Equation Modeling. Chapter 11: Path modeling: Structural equation modeling with measured variables. Chapter 12: Path analysis: Dangers and assumptions. Chapter 13: Analyzing path models using SEM programs. Chapter 14: Error: The scourge of research. Chapter 15: Confirmatory factor analysis I. Chapter 16: Putting it all together: Introduction to latent variable SEM. Chapter 17: Latent variable models: More advanced topics. Chapter 18: Latent means in SEM. Chapter 19: Confirmatory factor analysis II: Invariance and latent means. Chapter 20: Latent growth models. Chapter 21: Summary: Path analysis, CFA, SEM, and latent growth models. Appendices. Appendix A: Data files. Appendices B: Review of basic statistics concepts. Appendix C: Partial and semipartial correlation.