IAP BOOK SERIES
CILVR Series on Latent Variable Methodology
In order to stay at the forefront of their fields, applied researchers must keep their analytical toolkit up-to-date. One ever-expanding and increasingly critical part of this toolkit is the family of latent variable methods (e.g., structural equation modeling, latent growth modeling, latent class analysis). The reason for these methods’ importance is that they are uniquely adept at modeling constructs of theoretical interest but for which observable scores contain measurement error – a scenario that describes virtually all of the social and behavioral sciences, and well beyond. The CILVR Series on Latent Variable Methodology, with contributions from leading methodologists who are also skilled at translational writing, brings practical and theoretical advances in latent variable methods to graduate students, applied researchers, and methodologists alike, helping them to stay current as they move their respective disciplines forward.
Advances in Latent Class Analysis
A Festschrift in Honor of C. Mitchell Dayton
2019Gregory R. Hancock, University of Maryland; Jeffrey R. Harring, University of Maryland; George B. Macready, University of Maryland
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