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10-29-2013 04:28 AM

I have a dataset that contains count and person time information for an event (CMG) stratified by a number of different variables (e.g. age, calendar year, etc...). I am using PROC GENMOD to construct a poisson model, using log(person-time) as an offset variable. The data was over-dispersed so I had to scale by the deviance.

How can I use the basic model (with no exposure or covariates) to calculate the unadjusted incidence rate of CMG in the entire cohort (regardless of covariate profiles)? I know what the value should be but I would like to get it from the model and also look at the associated 95% confidence interval.

Here's the basic form of the model I'm using:

**PROC** **GENMOD** DATA=work.Count_PT_data

MODEL TotalCMG = / DIST=poi LINK=log offset=LOG_PT SCALE=deviance;

**RUN**;

Thanks for your help! Let me know if there's anything more I can post.

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Posted in reply to mconover

10-29-2013 10:56 AM

Consider adding the OBSTATS option. It will generate beaucoup output, with multiple variables included, but most importantly it will give X*beta and it's confidence limits. This should be identical for every observation with the intercept-only model that you have specified. The confidence bounds will be based on the rescaled error. I really think that the value with the intercept-only model will reflect the mean exposure in the dataset. To get the estimate with exposure set to zero, you could try (WARNING--untested code. Just because I think it ought to work doesn't guarantee that it will):

**PROC** **GENMOD** DATA=work.Count_PT_data

MODEL TotalCMG = **exposure**/ DIST=poi LINK=log offset=LOG_PT SCALE=deviance;

**LSMESTIMATE intercept 'Exposure=0' 1/at exposure=0 ilink;**

**RUN**;

Good luck.

Steve Denham

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Posted in reply to mconover

12-28-2013 05:25 AM

I have done the same analysis, in the way Steve Denham explains and it worked out well.

This topic is described here aswell: 24188 - Modeling a rate and estimating rates and rate ratios (with confidence intervals)