I have a categorical dependent variable that involves four clusters of positions. In descriptive analysis, I noticed that first cluster covered about 5% of the participants, second 6%, third 60%, and fourth 29%. I have four continuous independent variables and I am thinking of using multinomial logistic regression.
Do you think that low percentages in the first two clusters would be a problem? Should I omit the first two and turn the model into a binary logistic regression model predicting the probability of belonging to either the third or fourth cluster?