Applied Latent Class Analysis
Jacques A. Hagenaars, Allan L. McCutcheon
Cambridge University Press, Jun 24, 2002 - Social Science
Applied Latent Class Analysis introduces several innovations in latent class analysis to a wider audience of researchers. Many of the world's leading innovators in the field of latent class analysis contributed essays to this volume, each presenting a key innovation to the basic latent class model and illustrating how it can prove useful in situations typically encountered in actual research.
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alcohol algorithm applied approach assumed assumption B¨ockenholt cells Chapter chi-square chi-squared statistic Clogg concomitant variable conditional probabilities constraints contingency tables corresponding covariates cross-classified data degrees of freedom DeSarbo dichotomous distribution effects EM algorithm Equation example father’s schooling favorably endowed Figure frequencies function Goodman groups Hagenaars hazard model Heijden independence index of fit indicator variables Journal Langeheine latent budget latent class analysis latent class model latent Markov model latent status latent structure analysis latent variable Lazarsfeld LC cluster LC model likelihood linear logistic loglinear models manifest variables marijuana Markov chain method missing data mixed Markov model mixture index mixture models mixture regression models model H observed variables obtained parameter estimates parameterization population problem Rasch model ratio relationship Research response patterns response probabilities restrictions sample scores specified three-class tion transition probabilities Tried tobacco two-class unconstrained unobserved heterogeneity values Vermunt zero