Mplus Users Guide v6.. - Muthén & Muthén

Examples: Mixture Modeling With Cross-Sectional DataThe MODEL command does not need to be specified when automaticstarting values are used. The means and variances of the latent classindicators and the mean of the categorical latent variable are estimatedas the default. The means of the latent class indicators are not heldequal across classes as the default. The variances are held equal acrossclasses as the default and the covariances among the latent classindicators are fixed at zero as the default. The default estimator for thistype of analysis is maximum likelihood with robust standard errors. TheESTIMATOR option of the ANALYSIS command can be used to selecta different estimator. An explanation of the other commands can befound in Examples 7.1 and 7.3.EXAMPLE 7.10: LCA WITH CONTINUOUS LATENT CLASSINDICATORS USING USER-SPECIFIED STARTING VALUESWITHOUT RANDOM STARTSTITLE: this is an example of a LCA withcontinuous latent class indicators usinguser-specified starting values withoutrandom startsDATA: FILE IS ex7.10.dat;VARIABLE: NAMES ARE y1-y4;CLASSES = c (2);ANALYSIS: TYPE = MIXTURE;STARTS = 0;MODEL:%OVERALL%%c#1%[y1–y4*1];y1-y4;%c#2%[y1–y4*-1];y1-y4;OUTPUT: TECH1 TECH8;The difference between this example and Example 7.4 is that the latentclass indicators are continuous variables instead of binary variables. Asa result, starting values are given for means instead of thresholds.The means and variances of the latent class indicators and the mean ofthe categorical latent variable are estimated as the default. In the modelsfor class 1 and class 2, by mentioning the variances of the latent class159