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Latent class marginal regression models for modelling youthful drug involvement and its suspected influences
Author(s) -
Reboussin Beth A.,
Anthony James C.
Publication year - 2001
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.695
Subject(s) - categorical variable , latent class model , statistics , logistic regression , econometrics , latent variable , latent variable model , regression analysis , mathematics , set (abstract data type) , construct (python library) , class (philosophy) , regression , computer science , artificial intelligence , programming language
In longitudinal behavioural studies, it is common to have multiple categorical indicators for measuring a theoretical construct of interest. A latent class model is presented that accounts for the structure in a set of correlated, categorical variables measured at discrete time periods, drawing information from these variables to form a smaller number of latent classes. The dependence of the resulting latent class model parameters on suspected factors over time is simultaneously modelled using a baseline‐category logistic regression model. Estimation of the model parameters is achieved using an estimating equations procedure. A motivating example is provided from a longitudinal study of suspected linkages between monitoring or supervision by parents and the occurrence of drug use behaviours in an epidemiologic sample of school‐attending youths. Copyright © 2001 John Wiley & Sons, Ltd.