Mplus Users Guide v6.. - Muthén & Muthén

CHAPTER 15MIXTURE MODELSThere are three options that are used specifically for mixture models.They are CLASSES, KNOWNCLASS, and TRAINING.CLASSESThe CLASSES option is used to assign names to the categorical latentvariables in the model and to specify the number of latent classes in themodel for each categorical latent variable. This option is required forTYPE=MIXTURE. Between-level categorical latent variables must beidentified as between-level variables using the BETWEEN option.Following is an example of how the CLASSES option is used:CLASSES = c1 (2) c2 (2) c3 (3);where c1, c2, and c3 are the names of the three categorical latentvariables in the model. The numbers in parentheses specify the numberof classes for each categorical latent variable in the model. Thecategorical latent variable c1 has two classes, c2 has two classes, and c3has three classes.When there is more than one categorical latent variable in the model,there are rules related to the order of the categorical latent variables.The order is taken from the order of the categorical latent variables inthe CLASSES statement. Because of the order in the CLASSESstatement above, c1 is not allowed to be regressed on c2 in the model. Itis only possible to regress c2 on c1 and c3 on c2 or c1. This orderrestriction does not apply to PARAMETERIZATION=LOGLINEAR.KNOWNCLASSThe KNOWNCLASS option is used for multiple group analysis withTYPE=MIXTURE. The KNOWNCLASS option is used to identify thecategorical latent variable for which latent class membership is knownand equal to observed groups in the sample. Only one KNOWNCLASSvariable can be used. Following is an example of how to specify theKNOWNCLASS option:506