Hello,
I need some help with this problem i am trying to solve. I am running a logistic regresssion model. After running the full model, i removed one variable from the full model. I want to see how removing that one variable affected the betas (parameter estimates) of the other variables in the model.
I will be very grateful if i can get an answer to this.
Thanks
I modified the solution you gave and it worked perfectly well. Thank you so much for your input Reeza.
Below is the complete code for anyone with similar problem:
/*1*/
ods table parameterestimates=model1;
proc logistic data=temp;
class sex race hospital snf;
model read=sex race hospital snf;
run;
ods table parameterestimates=model2;
proc logistic data=temp;
class sex race hospital;
model read=sex race hospital;
run;
proc sort data=model1;
by variable;
proc sort data=model2;
by variable;
run;
data comparison;
/*2*/
merge model1 (Rename=estimate=estimate1)
model2 (rename=estimate=estimate2);
by variable;
/*3*/
diff=((estimate1-estimate2)/estimate2)*100;
run;
proc print data=comparison;
run;
Sorry, It's unclear what your question is. If you have a question on code, please include your current code.
Thank you for your response.
Assuming that i have a logisic regression model with the full model below:
proc logistic data=temp;
class sex race hospital snf;
model read=sex race hospital snf;
run;
and then i reduced model as below (it is without the variable snf)
proc logistic data=temp;
class sex race hospital;
model read=sex race hospital;
run;
I want to see how removing snf from the full model changed the betas (parameter estimates) for other variables in the reduced model.
/*1*/
ods table parameterestimates=model1;
proc logistic data=temp;
class sex race hospital snf;
model read=sex race hospital snf;
run;
ods table parameterestimates=model2;
proc logistic data=temp;
class sex race hospital snf;
model read=sex race hospital;
run;
data comparison;
/*2*/
merge model1 (Rename=estimate=estimate1)
model2 (rename=estimate=estimate2);
by variable;
/*3*/
diff=estimate1-estimate2;
run;
I modified the solution you gave and it worked perfectly well. Thank you so much for your input Reeza.
Below is the complete code for anyone with similar problem:
/*1*/
ods table parameterestimates=model1;
proc logistic data=temp;
class sex race hospital snf;
model read=sex race hospital snf;
run;
ods table parameterestimates=model2;
proc logistic data=temp;
class sex race hospital;
model read=sex race hospital;
run;
proc sort data=model1;
by variable;
proc sort data=model2;
by variable;
run;
data comparison;
/*2*/
merge model1 (Rename=estimate=estimate1)
model2 (rename=estimate=estimate2);
by variable;
/*3*/
diff=((estimate1-estimate2)/estimate2)*100;
run;
proc print data=comparison;
run;
Use backward seletion + include= option.
data class;
set sashelp.class;
if _n_ in (1:9) then y=1;
else y=0;
run;
proc logistic data=class;
class sex;
model y(event='1')= sex age weight height/details selection=backward include=3;
run;
Are you ready for the spotlight? We're accepting content ideas for SAS Innovate 2025 to be held May 6-9 in Orlando, FL. The call is open until September 16. Read more here about why you should contribute and what is in it for you!
Learn how use the CAT functions in SAS to join values from multiple variables into a single value.
Find more tutorials on the SAS Users YouTube channel.
Select SAS Training centers are offering in-person courses. View upcoming courses for: