I have a dataset with almost 300 cases and 8 variable. Some are binary, some are ordinal variables with 4 to 5 categories. I am performing a hierarchial cluster analysis and latent class analysis in R.
For the former I use gower distance and
hclust function in R. For the latent class analysis I use
poLCA package. The change in agglomeration coefficient after clustering and local minima of AIC after latent class analysis suggests the same number of latent groups (4) which is also in line with my pre-study beliefs.
However, after latent class analysis, the BIC have a perfect linear correlation with number of possible latent classes when interpreted graphically. There is no local minima present with up to 10 classes. How should I interpret this finding?