I am just starting to learn about the advanced methods of variable selection (lasso, lar, ridge,...). As a start I simply wanted to test the different functionalities of SAS and tried to implement a stepwise regression in PROC HPGENSELECT to compare with PROC LOGISTIC, since this is what both procedures offer. I know that for LASSO I have to use HPGENSELECT. But now few questions already arise:   1) I thought that these two syntaxes would do the same:   proc logistic data=TEST; class y x1 x2 x3 x4 x5 x6 x7 x8; model y = x1 x2 x3 x4 x5 x6 x7 x8 / link=logit selection=stepwise slentry=0.2 slstay=0.167 details lackfit; run; proc hpgenselect data=TEST; class y x1 x2 x3 x4 x5 x6 x7 x8; model y = x1 x2 x3 x4 x5 x6 x7 x8 / link=logit; selection method=stepwise(select=sl sle=0.2 sls=0.167 /*stop=SBC*/); performance details; run; Proc logisttic bases its decisions on p-values as required with the  select=sl in the second code (with same entry and exit levels). But results are different. Does the model or algorithm differe between these procedures, and how?   2) For an ordinal logistic regression, with ordinal IVs, must each variable be followed by an (param = ordinal)? E.g.   class y x1(param = ordinal) x2(param = ordinal) x3(param = ordinal) x4(param = ordinal) x5(param = ordinal) x6(param = ordinal) x7(param = ordinal) x8(param = ordinal);   Thanks in advance! ... View more

In proc glimmix multiple comparisons exist for lsmeans by pdiff combined with adjust, e.g. PDIFF=ALL ADJUST=bon (yes, tukey would be the better choice, still I'd like to use bonferroni). I can get the compact letter display (cld) with an additional lines statement. lsmeans f1*f2 / PDIFF=ALL ADJUST=bon LINES; With this code I request all tukey-comparisons (all combinations) but I am just interested in a few. Therefore I coded my comparisons of interest with lsmestimate. To adjust for multiple comparisons I use adjust=bon adjdfe=row.   lsmestimate f1*f2 'comp1' [1, 1 1] [-1, 2 1], 'comp2' [1, 1 1] [-1, 3 1], 'comp3' [1, 1 1] [-1, 4 1], 'comp4' [1, 2 1] [-1, 3 1], ... / cl adjust=bon adjdfe=row; Now my question: Is it possible to get a letter display only for those comparisons of interest and not all tukey-ones as in lsmeans? I somehow have to redefine the pdiff option but I am not aware how to easily solve that task. Any ideas on how to get such a table? I'd greatly appreciate it! ... View more