SAS Macro : Variable Selection based on Wald Chi-Square

Variable Selection based on Univariate Analysis (Wald Chi-Square and Standardized Coefficient)

PROC LOGISTIC is run on each of the variables and tracking p-value of wald chi-square and standardized coefficient,

%macro perf(data=,targetvar=,vars=,output=);

%let n=%sysfunc(countw(&vars));
%do i=1 %to &n;
%let val = %scan(&vars,&i);

ods select none;
ods output ParameterEstimates=Estimate&i;
proc logistic data=&data;
model &targetvar(event='1')=&val / stb;
run;

data Estimate&i;
set Estimate&i;
length Sig $15;
where Variable NE 'Intercept';
if ProbChiSq < .05 then Sig ='Significant';
else if ProbChiSq >= .05 then Sig = 'Non-Significant';
help = abs(StandardizedEst);
run;

%end;

data &output;
set Estimate1 - Estimate&n;
run;

proc datasets library=work
nodetails nolist;
delete Estimate1 - Estimate&n;
run;
quit;

proc sort data = &output;
by descending help;
run;

data &output;
set &output (drop = help DF);
run;

%mend perf;

options symbolgen mlogic;
%perf(data=imputed ,targetvar= ins,vars= mmbal income ilsbal posamt ,output= resultf);

About Author:
Deepanshu Bhalla

Deepanshu founded ListenData with a simple objective - Make analytics easy to understand and follow. He has over 10 years of experience in data science. During his tenure, he worked with global clients in various domains like Banking, Insurance, Private Equity, Telecom and HR.

While I love having friends who agree, I only learn from those who don't
Let's Get Connected Email LinkedIn