I did a study using Lighthouse Studio, but I evaluated it with R and the 'Apollo' package by Stephane Hess and David Palma. Whereas in Lighthouse Studio the covariates affect all part-worth utilities, 'Apollo' allows you to differentiate which attribute the individual covariates should affect.
I learned from the current scientific literature that only a few covariates with as much explanatory information as possible should be used. Now the following questions arise:
a) What happens if I add more covariates to the model? So far I have understood that in extreme cases the effects of the covariates are zero, i.e. not significant. However, can it happen that covariate A alone is significant, B alone is significant, but A and B together are not significant? In regression analyses, I know the problem of multicollinearity. Nevertheless, the HB model is different so I am not sure if I am on the safe side, even if A and B do not correlate.
b) Does the sample size have an influence on the number of covariates recommended?
I look forward to your answers.