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eBook An Introduction to Multilevel Modeling Techniques (Quantitative Methodology Series) ePub

eBook An Introduction to Multilevel Modeling Techniques (Quantitative Methodology Series) ePub

by Scott L. Thomas,Ronald H. Heck

  • ISBN: 1841697567
  • Category: Mathematics
  • Subcategory: Math Science
  • Author: Scott L. Thomas,Ronald H. Heck
  • Language: English
  • Publisher: Routledge; 2 edition (August 20, 2008)
  • Pages: 280
  • ePub book: 1318 kb
  • Fb2 book: 1479 kb
  • Other: lrf rtf doc lit
  • Rating: 4.1
  • Votes: 502

Description

Heck and Thomas provide an introduction to multilevel modeling that is not just comprehensive but also eminently readable. Heck is a great author and this covers many multi-level modeling techniques.

Heck and Thomas provide an introduction to multilevel modeling that is not just comprehensive but also eminently readable. Laura Stapleton, University of Maryland Baltimore County. Ronald H. Heck is professor of education at the University of Hawai‘i Manoa. I cannot imagine taking Structural Equation Modeling without this book.

An Introduction to Multilevel Modeling Techniques (The Quantitative Methodology Series). Heck, Scott L. Thomas. Download (epub, 670 Kb). FB2 PDF MOBI TXT RTF. It is an excellent choice for an instructor looking for a text that helps students to become facile with modeling choices and approaches.

Ronald H. Thomas

Ronald H. Univariate and multivariate multilevel models are used to understand how to design studies and analyze data in this comprehensive text distinguished by its variety of applications from the educational, behavioral, and social sciences. Basic and advanced models are developed from the multilevel regression (MLM) and latent variable (SEM) traditions within one unified analytic framework for investigating hierarchical data

Basic and advanced models are developed from the multilevel regression (MLM) and latent variable (SEM) traditions . Heck is professor of education at the University of Hawai'i at Manoa.

Basic and advanced models are developed from the multilevel regression (MLM) and latent variable (SEM) traditions within one unified analytic framework for investigating hierarchical data. Scott L. Thomas is professor and Dean of the School of Educational Studies at Claremont Graduate University.

Fuli Li. Xin Lai. Kwok Leung.

Multilevel Modeling Using R provides you with a helpful guide to conducting multilevel data modeling using the R. .

Multilevel Modeling Using R provides you with a helpful guide to conducting multilevel data modeling using the R software environment.

Author: Ronald H. Heck Scott L. Multilevel Modeling (Quantitative Applications in the Social Sciences) Content Analysis: An Introduction to It. Multilevel Modeling (Quantitative Applications in the Social Sciences). Dynamic Modeling: An Introduction (Quantitative Applications in the Social Sciences). Content Analysis: An Introduction to Its Methodology. Univariate and multivariate multilevel models are used to understand how to design studies and analyze data in this comprehensive text distinguished by its variety of applications from the educational, behavioral, and social sciences

Ronald H. Basic and advanced models are developed from the multilevel regression (MLM) and latent variable (SEM) traditions within one unified analytic framework for investigating hierarchical data

This comprehensive, applied approach to multilevel analysis is distinguished by its wide range of applications relevant to the behavioral, educational, organizational, and social sciences. Univariate and multivariate models are used to understand how to design studies and analyze data. Readers are encouraged to consider what they are investigating, their data, and the strengths and limitations of each technique before selecting their approach. Numerous examples and exercises allow readers to test their understanding of the techniques. Input programs from HLM and Mplus demonstrate how to set up and run the models.

A latent variable conceptual framework is emphasized to show the commonality of the approaches and to make each technique more accessible. The first section is devoted to conceptual issues underlying multilevel modeling, while the second section develops several types of multilevel analyses including univariate regression, structural equation, growth curve and latent change, and latent variable mixture modeling. The new edition features:

New chapters on multilevel longitudinal and categorical models 80% new exercises and examples website at http://www.psypress.com/multilevel-modeling-techniques/ providing datasets and program setups in HLM, SPSS, Mplus, and LISREL Increased emphasis on how multilevel techniques are used to examine changes in individuals and organizations over time.

Ideal for introductory graduate level courses on multilevel and/or latent variable modeling, this book is intended for students and researchers in psychology, business, education, health, and sociology interested in understanding multilevel modeling. Prerequisites include an introduction to data analysis and univariate statistics.

Comments

Golkree Golkree
Heck is a great author and this covers many multi-level modeling techniques. I cannot imagine taking Structural Equation Modeling without this book.
Ungall Ungall
Among many other sources, I used the first edition of this book when I was trying to teach myself multilevel modeling. I think it is probably a good book for a better informed reader, but it was too dense for a beginner. I was also disappointed to find that it devoted most of its 209 hundred pages to structural equation modeling and an unusually elegant treatment of multiple regression analysis. While the joining of multilevel modeling, factor analysis, and structural equation modeling were discussed in a no doubt suitable way, the development of multilevel modeling itself got much less attention than the title of the book suggested, and much less attention than I needed at the time. A second edition of the book, which I have not read, is now available.
Samugor Samugor
This isn't the most "introductory" introduction to multilevel modeling, but it's an excellent book. Heck and Thomas present multilevel models from an integrated structural equation modeling perspective, in the vein of Muthen and the Mplus software or Skrondal & Rabe-Hesketh and the GLLAM software.

The authors illustrate how traditional multilevel models, such as those estimated with the HLM software, can be extended to models with latent predictors and latent outcomes, and they describe advanced extensions (e.g., finite-mixture models and models with categorical indicators) as well as similarities with other methods (e.g., latent growth curve models). It is nice to find a book that is both conceptually integrative and practical.

If you plan to use Mplus for your multilevel analyses, this is the single best book to buy. If you're new to multilevel models, you should start with other books (such as Multilevel Modeling (Quantitative Applications in the Social Sciences)) before digging into this one.