I want to see how many profiles (latent classes) can be differentiated based on respondents’ patterns of responses to four binary variables (accepting or rejecting four different immigration policies).
In order to explore how many profiles are there, I ran several latent class analyses, asking for different number of classes. I used the poLCA package in R. Whenever I asked for more than 3 classes, there was a warning that residual degrees of freedom are negative. What does it mean?
Can I still use the model with negative df if the classes intuitively make sense? Is it possible to compare the model with negative df to other models to see which one better fits data?
Since I do not have any experience with the LCA, your help would be very much appreciated.