dcaputo,

I would drop the multidimensional arrays approach. You are presently computing N**2 as the number of variables in the multidimensional array. Instead of passing N**2, why not compute and pass N*(N-1)/2 as the number of interactions. When constructing the interactions, loop from I=1 to &numvar-1 and J=I+1 to &numvar. You also need to form a counter which keeps track of how far into the unidimensional array you are with the current interaction term. Here is some revised code.

data _null_; numint = &numvar*(&numvar-1)/2; call symput('numint',trim(left(numint))); run;

data logit.abc; set logit.ss; array itr{&numint} itr1 - itr&numint; array col{&numvar} col1 - col&numvar;

k=0; do i = 1 to &numvar-1; do j = i+1 to &numvar; k=k+1; itr{k} = col{i}*col{j}; end; end; run;

Although you have not asked about this, let me make a few more comments on your code. The process which you use to determine the number of variables on the right hand side of your model uses a lot more resources than necessary. Rather than transposing the entire dataset logit.Z_inter, why not transpose one observation from logit.Z_inter?

proc transpose data=logit.Z_inter(obs=1) out=numvar(drop=_name_); var &final; run;

Later in your code, you use the transpose of dataset NUMVAR (logit.ss) as input to a datastep where you construct the interaction effects. Well, the transpose of NUMVAR should return logit.Z_inter. So, datastep logit.abc can use as input logit.Z_inter rather than dataset logit.ss. You can get rid of one proc transpose entirely, and reduce one proc transpose to a trivial problem. That should really speed up your processing.

In addition, you do not need the statement which appears in your SQL code

%let numvar=&numvar;

Dale

-------------------------------------- Dale McLerran Fred Hutchinson Cancer Research Center Seattle, WA 98109 mailto:dmclerra@fhcrc.org ph: (206) 667-2926 fax: (206) 667-5977 --------------------------------------

dcaputo@banet.net wrote in <39BC2AAC.B0E32A67@banet.net>:

>The goal is to take a dataset with N columns and to form N(N-1)/2 other >columns that represent the 2-Way interactions of the variables in the >original N columns. The program I have written so far creates N*N >variables or new columns with a DO LOOP within a DO LOOP. Picture this >as an N by N matrix, Xij. I want to change the program to output only >those columns Xij where i > j. I tried a DROP in the DO LOOP but it >doesn't work. > > > > HELP! > > >/* target variable */ > > %let target = ins; > > >/* final model covariates */ > >%let final = var1 var2 var3 var4; > > > >/* create SAS dataset with reduced variables only */ > >data logit.Z_inter; > set logit.A_ins (keep = &target &final); >run; > > >proc transpose data=logit.Z_inter out=numvar (drop=_name_); > var &final; >run; > > > >/* compute the number of variables in the final model and place in macro >variable */ > > proc sql noprint; > select > count(*) > > into > :numvar > > from > numvar; > > %let numvar = &numvar; >quit; > > > > >proc transpose data=numvar out=logit.ss (drop=_name_); >run; > > > >/* compute number of elements in the square matrix > > >data _null_; > numint = &numvar*&numvar; > call symput('numint',trim(left(numint))); >run; > > > >data logit.abc; > set logit.ss; > array itr{&numvar,&numvar} itr1 - itr&numint; > array col{&numvar} col1 - col&numvar; > > do i = 1 to &numvar; > > do j = 1 to &numvar; > > itr{i,j} = col{i}*col{j}; > > end; > end; >run;