I have a data set of 274 people with 137 cases and 137 controls matched on w, x, y and z. I am doing a conditional logistic for multiple different exposures and testing effect measure modification by sex. I was going to check confounding too (related to x, related to y among unexposed and not on the causal pathway) but I am coming up with very odd values in my output. It says that the convergence criterion is satisfied and the data seems to be formatting correctly and there are no missing values.
This is my code:
proc logistic data=data; /*outcome = suicide. exposure = sex*/
strata ccmatchid;
model sample_index (event='1') = b_dm02; run;
Odds Ratio Estimates Effect
b_DM02
Point Estimate
>999.999
95% Wald Confidence Limits
<0.001 >999.999
Solved: The participants were matched on sex apparently so of course you couldn't add it as an effect modifier....
The odds ratio is the ratio of two numbers. It looks like the denominator is zero or very close to zero. The estimate for the odds ratio is very big ("infinity") which is displaying as > 999.999.
The Wald confidence interval about 1 is similalry undefnied. Essentially you can interpret it as (0, infinity), which gives you no information.
It is indicative of a larger problem, no? I should be able to easy test to see if sex is a predictor of suicide. I need to include it in all of my conditional logisit models (testing for effect measure modification). The variable works with McNemar's test so it doesn't seem to be a variable-level issue.
Solved: The participants were matched on sex apparently so of course you couldn't add it as an effect modifier....
Don't miss out on SAS Innovate - Register now for the FREE Livestream!
Can't make it to Vegas? No problem! Watch our general sessions LIVE or on-demand starting April 17th. Hear from SAS execs, best-selling author Adam Grant, Hot Ones host Sean Evans, top tech journalist Kara Swisher, AI expert Cassie Kozyrkov, and the mind-blowing dance crew iLuminate! Plus, get access to over 20 breakout sessions.
ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.
Find more tutorials on the SAS Users YouTube channel.