9780367182441-0367182440-An Introduction to Multilevel Modeling Techniques: MLM and SEM Approaches (Quantitative Methodology Series)

An Introduction to Multilevel Modeling Techniques: MLM and SEM Approaches (Quantitative Methodology Series)

ISBN-13: 9780367182441
ISBN-10: 0367182440
Edition: 4
Author: Heck, Ronald H., Thomas, Scott L.
Publication date: 2020
Publisher: Routledge
Format: Paperback 404 pages
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Book details

ISBN-13: 9780367182441
ISBN-10: 0367182440
Edition: 4
Author: Heck, Ronald H., Thomas, Scott L.
Publication date: 2020
Publisher: Routledge
Format: Paperback 404 pages

Summary

Acknowledged authors Heck, Ronald H., Thomas, Scott L. wrote An Introduction to Multilevel Modeling Techniques: MLM and SEM Approaches (Quantitative Methodology Series) comprising 404 pages back in 2020. Textbook and eTextbook are published under ISBN 0367182440 and 9780367182441. Since then An Introduction to Multilevel Modeling Techniques: MLM and SEM Approaches (Quantitative Methodology Series) textbook was available to sell back to BooksRun online for the top buyback price or rent at the marketplace.

Description

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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