SELECTION=BACKWARD is usually a bad idea when there are many candidate effects in the model. The reason it is a bad idea is that the method starts with the most complex model which includes all of the candidate effects. This model is usually so complex and makes the data so sparse that the maximum likelihood solution does not exist. Better to use SELECTION=FORWARD or STEPWISE which starts with no effects (or only those forced by the INCLUDE= option) and built up a model. ... View more