Simulations in SAS

Binomial Data & Logistic Regression

/** Simulate binomial data, then analyze it it with Logistic Regression **/
/*  Simulate dataset */
%let N=150;
data LogisticData;
array xx1{&N} _temporary_;
array xx2{&N} _temporary_;
call streaminit(1);
/* simulate fixed effects */
do i=1 to &N;
xx1{i}=rand("Uniform");
xx2{i}=rand("Normal", 0 , 2);
end;
/*Simulate Logistic Model */
do i=1 to &N;
x1=xx1{i};
x2=xx2{i};
eta=2-4*x1+1*x2; 
mu=exp(eta)/(1+exp(eta)); 
y=rand("Bernoulli", mu);
output;
end;
run;
/* median probability across probabilities */
proc means data=logisticdata median;
var mu; 
run; 
proc freq data=logisticdata; 
table y / plots=FreqPlot(scale=percent);
run; 
proc logistic data=logisticdata plots=all;
model y(Event='1')=x1 x2 / aggregate=x1 scale=none influence;
output out=logistic_out xbeta=xbeta;
ods output Influence=Logistic_Influence; 
run;