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

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

A Multigroup Exploratory Latent Class Analysis. Multigroup latent class analysis identified two BI-Court subgroups of youth and three truant subgroups. Friday, November 2, in Cleveland Hall 418. Candidate at North Carolina State University, at 3:00 p.m. 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. This is the first time, to the authors' knowledge, that latent class analysis has been applied to longitudinal data on back pain patients. Abstract: When data are believed to have hidden clusters, it is common practice to identify the clusters and then conduct analysis in each cluster separately. 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. 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. Please join us for the applied mathematics talk "Penalization Techniques for Latent Class Regression," presented by Anthony Franklin, a Ph.D. A website features some of the data sets and syntax commands used in the book. Classifications of these subgroups were based on their psychosocial characteristics (e.g., substance use).