SAS Macro : Variable Selection based on Wald Chi-Square

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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);

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Deepanshu founded ListenData with a simple objective - Make analytics easy to understand and follow. He has close to 7 years of experience in data science and predictive modeling. During his tenure, he has worked with global clients in various domains like retail and commercial banking, Telecom, HR and Automotive.


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