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Education & Reference - Growth Modeling: Structural Equation and Multilevel Modeling Approaches (Methodology in the Social Sciences)

Description

Book Synopsis: Growth models are among the core methods for analyzing how and when people change. Discussing both structural equation and multilevel modeling approaches, this book leads readers step by step through applying each model to longitudinal data to answer particular research questions. It demonstrates cutting-edge ways to describe linear and nonlinear change patterns, examine within-person and between-person differences in change, study change in latent variables, identify leading and lagging indicators of change, evaluate co-occurring patterns of change across multiple variables, and more.

User-friendly features include real data examples, code (for Mplus or NLMIXED in SAS, and OpenMx or nlme in R), discussion of the output, and interpretation of each model's results.

User-Friendly Features:

  • Real, worked-through longitudinal data examples serving as illustrations in each chapter.
  • Script boxes that provide code for fitting the models to example data and facilitate application to the reader's own data.
  • "Important Considerations" sections offering caveats, warnings, and recommendations for the use of specific models.

Companion website supplying datasets and syntax for the book's examples, along with additional code in SAS/R for linear mixed-effects modeling.

Winner--Barbara Byrne Book Award from the Society of Multivariate Experimental Psychology

Details

Are you looking for a comprehensive guide to analyzing how people change over time? Look no further! Our book, "Growth Modeling: Structural Equation and Multilevel Modeling Approaches," will walk you through step by step to apply cutting-edge techniques to longitudinal data. Whether you're a researcher or a student, this book is perfect for anyone interested in understanding linear and nonlinear change patterns. With real data examples and code in Mplus, NLMIXED, OpenMx, and nlme, you'll be able to put theory into practice with ease.

What sets this book apart are the user-friendly features designed to enhance your learning experience. Each chapter includes real longitudinal data examples, providing practical illustrations throughout. You'll also find script boxes with code to fit the models to example data, making it easier for you to apply the techniques to your own research. Additionally, "Important Considerations" sections offer valuable caveats, warnings, and recommendations to ensure you make the most of each model.

As a winner of the esteemed Barbara Byrne Book Award from the Society of Multivariate Experimental Psychology, you can trust in the quality and relevance of the content. We understand that growth modeling can be complex, but our book simplifies the process, allowing you to gain a deeper understanding of change in latent variables, identify leading indicators of change, and evaluate patterns across multiple variables.

Don't miss out on this valuable resource! Click here to get your copy of "Growth Modeling: Structural Equation and Multilevel Modeling Approaches" and take your research to the next level.

Disclosure: I get commissions for purchases made through links in this website