An Introduction to Multilevel Modeling Techniques: MLM and SEM Approaches Using Mplus

4th Edition

Ronald H. Heck, Scott L. Thomas

Routledge
March 25, 2020 Forthcoming
Textbook - 440 Pages - 59 B/W Illustrations
ISBN 9780367182441 - CAT# K416365
Series: Quantitative Methodology Series

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Summary

Multilevel modelling is a data analysis method that is frequently used to investigate hierarchal data structures in educational, behavioural, health, and social sciences disciplines. Multilevel data analysis exploits data structures that cannot be adequately investigated using single-level analytic methods such as multiple regression, path analysis, and structural modelling. This text offers a comprehensive treatment of multilevel models for univariate and multivariate outcomes. It explores their similarities and differences and demonstrates why one model may be more appropriate than another, given the research objectives.

New to this edition:

  • An expanded focus on the nature of different types of multilevel data structures (e.g., cross-section, longitudinal, cross-classified, etc.) for addressing specific research goals
  • Varied modelling methods for examining longitudinal data including random-effect and fixed-effect approaches
  • Expanded coverage illustrating different model-building sequences and how to use results to identify possible model improvements
  • An expanded set of applied examples used throughout the text
  • Use of four different software packages (i.e., Mplus, R, SPSS, Stata), with selected examples of model-building input files included in the chapter appendices and a more complete set of files available online

This is an ideal text for graduate courses on multilevel, longitudinal, latent variable modelling, multivariate statistics, or advanced quantitative techniques taught in psychology, business, education, health, and sociology. Recommended prerequisites are introductory univariate and multivariate statistics.

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