Hello, I was advised to use PROC HPSPLIT to classify/categorise respondents. I have one ordinal DV (delivery rating) and varied IVs (binary, ordinal, nominal and continuous). Can Proc HPSPLIT help in classifying/categorising the respondents into 'delivery rating' based on the available IVs? I used proc hpsplit data=hpsplit.data; class del_rating; model del_rating = pckg_qual prcl_cond del_time del_loc max_del_time max_pc_wgt pc_count; grow entropy; prune costcomplexity (leaves=10); run; It of course produced outputs that I could not interpret. For e.g., the 'Classification Tree for Del_Rating' or the 'Subtree starting at Node=0' I'm aware of CHAID analysis, however, I have never used this procedure before. The first predictor category that CHAID uses to split the sample is the IV that is associated the most with the DV, i.e., it gives the most differentiating groups of respondents. Is it somethign similar? Could you please help me with choosing the right criterion for deciding on the split? Must I choose the 'leaves'? Or is there an option, wherein it stops producing the 'child' node until the algorithm does not find any significantly discriminating predictor any more? Apologies for posing such naive questions. I thank you in advance. MS
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