nested/more efficient macro for proc logistic

[Caetreviop543]

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I have two different data sets, six different outcome variables, and two primary (separate) predictors which I am trying to incorporate into proc logistic along with several covariates using a macro. I'm trying to figure out the most efficient way. My initial thought was: %macro mod(dat, out, pred); proc logistic data=&dat; model &out=&pred cov1 cov2 cov3 cov4 cov5 cov6 /desc; run; %mend mod; %mod (dat1, out1, pred1); %mod (dat1, out2, pred1); %mod (dat1, out3, pred1); %mod (dat1, out4, pred1); %mod (dat1, out5, pred1); %mod (dat1, out6, pred1); %mod (dat1, out1, pred2); %mod (dat1, out2, pred2); %mod (dat1, out3, pred2); %mod (dat1, out4, pred2); %mod (dat1, out5, pred2); %mod (dat1, out6, pred2); %mod (dat2, out1, pred1); %mod (dat2, out2, pred1); %mod (dat2, out3, pred1); %mod (dat2, out4, pred1); %mod (dat2, out5, pred1); %mod (dat2, out6, pred1); %mod (dat2, out1, pred2); %mod (dat2, out2, pred2); %mod (dat2, out3, pred2); %mod (dat2, out4, pred2); %mod (dat2, out5, pred2); %mod (dat2, out6, pred2); Is there a more efficient way, by referring to the outcome variables only once/nesting the macro? Another, however also inefficient, way is: %macro mod(out); proc logistic data=data_one; model &out=pred1 cov1 cov2 cov3 cov4 cov5 cov6/desc; run; proc logistic data=data_one; model &out=pred2 cov1 cov2 cov3 cov4 cov5 cov6/desc; run; proc logistic data=data_two; model &out=pred1 cov1 cov2 cov3 cov4 cov5 cov6/desc; run; proc logistic data=data_two; model &out=pred2 cov1 cov2 cov3 cov4 cov5 cov6/desc; run; %mend mod; %mod (out1); %mod (out2); %mod (out2); %mod (out3); %mod (out4); %mod (out5); %mod (out6); Thanks in advance! Em

[Caetreviop543]

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Hello, I have two data sets, six different outcome variables, and two primary (separate) predictors which I am trying to incorporate into proc logistic along with several covariates using a macro. I'm trying to figure out the most efficient way. My initial thought was: %macro mod(dat, out, pred); proc logistic data=&dat; model &out=&pred cov1 cov2 cov3 cov4 cov5 cov6 /desc; run; %mend mod; %mod (dat1, out1, pred1); %mod (dat1, out2, pred1); %mod (dat1, out3, pred1); %mod (dat1, out4, pred1); %mod (dat1, out5, pred1); %mod (dat1, out6, pred1); %mod (dat1, out1, pred2); %mod (dat1, out2, pred2); %mod (dat1, out3, pred2); %mod (dat1, out4, pred2); %mod (dat1, out5, pred2); %mod (dat1, out6, pred2); %mod (dat2, out1, pred1); %mod (dat2, out2, pred1); %mod (dat2, out3, pred1); %mod (dat2, out4, pred1); %mod (dat2, out5, pred1); %mod (dat2, out6, pred1); %mod (dat2, out1, pred2); %mod (dat2, out2, pred2); %mod (dat2, out3, pred2); %mod (dat2, out4, pred2); %mod (dat2, out5, pred2); %mod (dat2, out6, pred2); Is there a more efficient way, by referring to the outcome variables only once/nesting the macro? Another, however also inefficient, way is: %macro mod(out); proc logistic data=data_one; model &out=pred1 cov1 cov2 cov3 cov4 cov5 cov6/desc; run; proc logistic data=data_one; model &out=pred2 cov1 cov2 cov3 cov4 cov5 cov6/desc; run; proc logistic data=data_two; model &out=pred1 cov1 cov2 cov3 cov4 cov5 cov6/desc; run; proc logistic data=data_two; model &out=pred2 cov1 cov2 cov3 cov4 cov5 cov6/desc; run; %mend mod; %mod (out1); %mod (out2); %mod (out2); %mod (out3); %mod (out4); %mod (out5); %mod (out6); Thanks in advance! Em

[Reeza · Accepted solution]

Or, don't write a macro and transform your data and use a BY statement.

https://communities.sas.com/t5/SAS-Communities-Library/How-do-I-write-a-macro-to-run-multiple-regres...

[Caetreviop543]

That's interesting! I wouldn't have thought to do it that way...

Thanks Reeza!