I have a data set comprising of real valued variables X (Range :-200 to 200 approximately) and ordered categorical response variables Y [1,2,3,4 or 5].
I want to predict the probability of getting response Yi given an input X. My question concerns whether a probit or logit model is more appropriate, i.e. on what basis(es) I should make this decision. If the log-likelihood is higher for one of the models does that imply that it is better, or am I being too simplistic? Do I need to look at the distribution of the independent variable X? If I introduce another input variable X2, which causes the log-likelihood to decrease, does this imply the single variable model is a better predictor of Y? Many thanks for your help, as you can probably tell I am not a statistician! . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
