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An Introduction to Multilevel Modeling Techniques - MLM and SEM Approaches (Hardcover, 4th edition)
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An Introduction to Multilevel Modeling Techniques - MLM and SEM Approaches (Hardcover, 4th edition)
Series: Quantitative Methodology Series
Expected to ship within 12 - 17 working days
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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-sectional, 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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