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Advances in Latent Class Analysis - A Festschrift in Honor of C. Mitchell Dayton (Paperback)
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Advances in Latent Class Analysis - A Festschrift in Honor of C. Mitchell Dayton (Paperback)
Series: CILVR Series on Latent Variable Methodology
Expected to ship within 10 - 15 working days
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What is latent class analysis? If you asked that question thirty or
forty years ago you would have gotten a different answer than you
would today. Closer to its time of inception, latent class analysis
was viewed primarily as a categorical data analysis technique,
often framed as a factor analysis model where both the measured
variable indicators and underlying latent variables are
categorical. Today, however, it rests within much broader mixture
and diagnostic modeling framework, integrating measured and latent
variables that may be categorical and/or continuous, and where
latent classes serve to define the subpopulations for whom many
aspects of the focal measured and latent variable model may differ.
For latent class analysis to take these developmental leaps
required contributions that were methodological, certainly, as well
as didactic. Among the leaders on both fronts was C. Mitchell
"Chan" Dayton, at the University of Maryland, whose work in latent
class analysis spanning several decades helped the method to expand
and reach its current potential. The current volume in the Center
for Integrated Latent Variable Research (CILVR) series reflects the
diversity that is latent class analysis today, celebrating work
related to, made possible by, and inspired by Chan's noted
contributions, and signaling the even more exciting future yet to
come.
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