Dear Linda, Bengt, I fitted several factor mixture models using Mplus and obtained estimated conditional item probabilities for the best fitting model (i.e. estimated probabilities for each class integrated over the factor). My question concerns the standard errors for these conditional item probabilities, that is, the standard errors for the probabilities are missing in the output, because I used numerical integration to estimate the model (On the forum I read that Mplus does not give standard errors in the output when using numerical integration). Based on the conditional item probability plot there seem to be (minor) differences between classes. However, now I am unsure how to interpret differences these differences without standard errors or any other statistic. Can I just assume these probabilities differ between classes based on the plot only? Or do I have to test whether the non-significant thresholds differ between classes significantly using for instance the MODEL TEST option of Mplus? Some more information about the model: thresholds are fixed across classes for categorical indicators, and next to these categorical indicators I included various continuous indicators with class-varying intercepts, residual variances. Factor means are fixed at zero and factor variances at one. The model has two classes, and one factor within each class. I am using Mplus version 6.1. Thank you in advance!