FMM can be specified with class specific or class invariant parameters, such as factor loadings, means, variances, and item thresholds. Different levels of measurement invariance were tested for the 2 class, 1 factor model, including class specific thresholds, variances, means and loadings, and various combinations of these (for instance, class specific thresholds and loadings). In order to ensure that the model did not converge on local maxima, all 2 class, 1 factor models were run with 200 initial stage random sets of starting values, and 20 final stage optimizations. The best fitting FMM was subsequently run with 1000 initial stage random sets of starting values, 60 final stage optimizations and 60 initial stage iterations. The final stage solutions all had the same loglikelihood value, suggesting that the global maximum had been identified [45]. The model estimation terminated normally.
