when comparing LCGA models with different number of classes, when it comes to choose the best model, which indices should I base my decision on? I saw in other threads that entropy is not necessarily the best index to take into account. Can I rely on BIC?
I also saw that I could use TECH11 and TECH14 to compare models with models with k-1 class. How do you decide which model to choose when TECH11 and TECH14 have different conclusions (TECH11 with p value > .05 and TECH 14 witzh p < .05)?
Besides BIC, are there any other metrics we can use to compare models? I'm trying to compare LCGA models where one has a linear transformation on the x-axis and another has a square-root transformation on the x-axis.
Just to clarify, in order to determine if the linear or square-root transform work better, we need to compare the summed residual between the two models, right? And the residuals for each class in each model are given by the OUTPUT RESIDUAL command?