/*--------
|fitting logitstic regression to smoking data and loglinear model
-------------*/
options ls=90 nocenter nodate;

/**********************************************************/
/* fitting to 2x2 table */
data smoke;
input s $ y n ;
cards;
smoke 816 4019
nosmoke 188 1356
;
proc logistic data=smoke descending;
class s (ref=first) / param=ref;
model y/n = s /scale=none;
output out=predict pred=prob;
title 'Logistic regression for 2x2 table';
run;
proc print data=predict;
run;

/*without intercept*/
proc logistic data=smoke descending;
class s (ref=first)/param=ref;
model y/n= /scale=none;
title 'Logistic regression without intercept';
run;

proc genmod data=smoke;
class s;
model y/n = /link=logit dist=binomial;
title 'Logistic regression with PROC GENMOD';
run;

/******************************************************/
/* log-linear model of indepedence 2x2 table */
data smoke;
input s $ y $ count;
datalines;
smoke yes 816
smoke no 3203
nosmoke yes 188
nosmoke no 1168
;
proc genmod data=smoke order=data;
class s y;
model count = s y /link=log dist=poisson lrci type3 obstats;
title 'Loglinear model of indepedence';
run;