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2010 Feb 24
0
Extracting individual parameter estimates from mmlcr
...d, and BIC. For example, here is a cubic 3-class model I am using. mmlcr1 <- mmlcr(outer = ~ 1 | ID, components = list(list(formula = Score ~ poly(wave,3), class = "cnormlong", min = 1, max = 4)), data = datlong, n.groups = 3) In this model I can find these parameters as follows: mmlcrl$df mmlcr1$loglikelihood mmlcr1$BIC And I can identify individual parameter estimates such as posterior probabilities of belonging to specific classes, specific data points, corresponding fitted and residual values as follows: #posterior probability of belonging to class 1 summary.mmlcr(mmlcr1)[7...