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Applied Latent Class Analysis ebook download

Applied Latent Class Analysis by Allan L. McCutcheon, Jacques A. Hagenaars

Applied Latent Class Analysis

Download eBook

Applied Latent Class Analysis Allan L. McCutcheon, Jacques A. Hagenaars ebook
Format: pdf
Page: 478
ISBN: 0521594510, 9780521594516
Publisher: Cambridge University Press

4.5 In all three studies, securing samples of young people (and employers) was problematic. This is the first time, to the authors' knowledge, that latent class analysis has been applied to longitudinal data on back pain patients. The knowledge from data/database (KDD) framework for preparing data and finding patterns in large amounts of data served as the process framework in which a latent class analysis (LCA) was applied to IA user data. To explore the heterogeneity of APED use patterns, the authors subjected data on use patterns to (a) latent class analysis (LCA), (b) latent trait analysis (LTA), and (c) factor mixture analysis to determine the best model of APED use. A latent class regression (LCR) model, using 9 BRFSS HRQOL indicators, was used to determine latent classes of HRQOL for RI adults and to model the relationship between latent class membership and covariates. The goal of the latent class analysis is to simply classify the reentry experiences with system involvement that follows each exit. BRFSS interviewed 3,999 respondents. It is common in latent class analysis to fit models with different numbers of classes and compare them by Bayesian information criterion (BIC) and choose the model with the smallest BIC values [37,38]. Applied Latent Class Analysis introduces several innovations in latent class analysis to a wider audience of researchers. We develop a latent class modeling approach for joint analysis of high-dimensional semicontinuous biomarker data and a binary disease outcome. Richard Dembo⇓; Rhissa Baseline data collected in two brief intervention projects (BI-Court and Truancy Project) were used to assess similarities and differences in subgroups of at-risk youth. 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. Latent class analysis was used to identify sub-groups within the group of young people who were in JWT. Terms used are Latent Class Analysis (LCA) and Mixture Modeling (MM) (sometimes Finite MM). Multigroup latent class analysis identified two BI-Court subgroups of youth and three truant subgroups. Classifications of these subgroups were based on their psychosocial characteristics (e.g., substance use). 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. A Multigroup Exploratory Latent Class Analysis.