Applied Latent Class Analysis Allan L. McCutcheon, Jacques A. Hagenaars
Publisher: Cambridge University Press

In applying the proposed approach to an epidemiological study that examined the relationship between environmental polychlorinated biphenyl (PCB) exposure and the risk of endometriosis, we identified a highly significant overall effect of PCB concentrations on the risk of endometriosis. We develop a latent class modeling approach for joint analysis of high-dimensional semicontinuous biomarker data and a binary disease outcome. Latent class analysis (LCA) was used to group all GOLDN individuals according to the diameter of their fasting (8-hour fast) VLDL, LDL and HDL particles, determined by nuclear resonance spectroscopy. There is a growing gulf between the elite and the lower classes, and what used to be termed the middle and working classes seem to be splintering into social classes with systematically differing amounts of cultural and social capital. 4.5 In all three studies, securing samples of young people (and employers) was problematic. The Great British Class Using latent class analysis on measures of economic, social and cultural capital, from our nationally representative sample, we defined a new model of class in Britain today. Applications from the behavioral and social sciences The book is divided into techniques for analyzing cross-cultural data within the generalized-latent-variable approach: multiple-group confirmatory factor analysis and multiple-group structural equation modeling; multi-level analysis; latent class analysis; and item-response theory. The goal of the latent class analysis is to simply classify the reentry experiences with system involvement that follows each exit. A latent variable modeling approach, specifically latent class analysis (LCA), was used to generate profiles of youth based on their endorsements of the physical and sexual abuse items. Latent class analysis was used to identify sub-groups within the group of young people who were in JWT. A website features some of the data sets and syntax commands used in the book. We compare two techniques that are widely used in the analysis of life course trajectories: latent class analysis and sequence analysis. Applying latent class analysis to this data, six classes were identified as clinically interpretable and relevant subgroups of prescription opioid abusers. Next, the researchers applied latent class growth analysis to estimate the smoking trajectory for each individual. An alternative is to use the Expectation Maximization (EM) algorithm [26], which is also a maximum likelihood approach but ideally suited to problems comprising latent class variables, which is exactly what we have here as the true disease status of each observation is only latently While the DIC is very commonly used in Bayesian analyses, and is straightforward to estimate, it is not without its critics and its reliability in some situations is an active area of statistical research (e.g. Latent class analysis (LCA) was used to identify distinct patterns of known risk factors for suicide among the decedents and to classify these decedents by these patterns.