I've read that it is possible to have insignificant attributes in latent class which were significant in the logit analysis, is this correct? In my logit analysis all my attributes were significant, but I am not sure if this is still the case.

Do you have an example of a calculation or can you explain how to calculate whether the attributes are significant in the segments or not?

Many thanks in advance

Now, if you ran a 4-group latent class solution and you see for a given attribute that all of its levels have t<|1.96| for all four segments, then you would question whether this attribute should be in the model or not. But, if for even one group this attribute had for even one of its levels a significant t, then you would think that it is probable that this attribute adds fit to the model.

The more appropriate test for figuring out if an attribute adds significant fit to the model is by comparing the overall LL fit of the model with and without that attribute added. Two times the difference in LL between those two latent class runs is distributed as Chi square, with degrees of freedom equal to the number of additional parameters in the model for that attribute included vs. not included.