I am performing a latent class analysis with covariates. I want to calculate the predicted probabilities for the membership to different classes. However, if the order of the classes changes (as I rerun the model) I obtain different results for the predicted probability of the same class but in a different order. Does anyone encountered this problem before? I increased the number of maximum iterations in the model, but it does not seem to help. Also the classes' composition changes slightly when I rerun the model.
f <- cbind(a1, a2, a3, a4) ~ sex + age + age_sq + inc lc <- poLCA(f, mydata, nclass=3, graphs=TRUE, maxiter=50000)
inc varies between 1 and 4. This is the class composition, for example:
$a1 Pr(1) Pr(2) Pr(3) Pr(4) class 1: class 2: class 3: $a2 ....