Modeling Longitudinal and Multilevel Data

This book offers practical guidance on analyzing longitudinal and multilevel data, featuring various techniques and accessible resources for researchers and students.

In Modeling Longitudinal and Multilevel Data, experts provide a comprehensive guide to practical analytic approaches for handling complex data sets. The book covers various techniques, including Structural Equation Modeling (SEM), Latent Transition Analysis (LTA), Generalized Linear Models (GLM), and multi-level modeling. Each chapter offers valuable insights, tips, and real-world applications, making it an essential resource for graduate students and researchers in the social and behavioral sciences.

This work emphasizes the practical challenges associated with longitudinal and multilevel data analysis. It ensures that all data sets and corresponding command files are readily accessible online, allowing users to replicate and explore the working examples provided. The book supports four major SEM packages—LISREL, EQS, MX, and AMOS—as well as two multi-level packages—HLM and MLn—facilitating a hands-on learning experience. The standardized equations and conventions across contributions enhance clarity and understanding.

Modeling Longitudinal and Multilevel Data is designed to be user-friendly, making it suitable for both seasoned researchers and newcomers to the field. Readers can easily compare and contrast different analytic approaches, enriching their understanding of how to effectively analyze longitudinal and multiple-group data. This book stands as a vital tool for anyone looking to deepen their expertise in data analysis within the social and behavioral sciences.