CIs on Regression Coefficients from SAS Proc Logistic

[stat12000]

All-

I ran a simple logistic regression in SAS to obtain the CIs on the regression coefficients. The CIs do not appear to be correct. Can anyone let me know what they think is going on. If you calculate the CIs by hand, these do not match what is provided in the SAS output.

Analysis of Maximum Likelihood Estimates
Parameter	DF	Estimate	Standard Error	Wald Chi-Square	Pr > ChiSq
Intercept	1	7.6653	22.9839	0.1112	0.7388
x	1	-1.1236	3.3681	0.1113	0.7387

Parameter Estimates and Wald Confidence Intervals
Parameter	Estimate	95% Confidence Limits
Intercept	7.6653	-37.3823	52.7128
x	-1.1236	-7.7250	5.4779

By hand, I get the 95% (2-sided) CI for the intercept: (-52.71234 ,  37.38174 )

SAS Code: 

proc import datafile="C:\Users\BodnarJ\Desktop\functionalRequirement4_9_X\dataSim_FR_4_9_X.csv" dbms=csv out=work.anaDS replace;
delimiter="|";
getnames=yes;
guessingrows=7000;
run;

proc logistic data = anaDS ;
model yBinom1 = x / cl;
output out=propensity_scores pred=prob_flag;
run;

[PaigeMiller]

Typically, the actual estimated coefficient for a logistic regression is approximately half-way between the upper confidence interval and the lower confidence interval.

Therefore, I conclude that your hand calculations are wrong.

[PGStats · Accepted solution]

You must be modelling for the yBinom1=0 events. Try the syntax

model yBinom1(event='1') = x / cl;

[ajkalale]

The above solution is absolutely correct!