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I want to estimate risk for a certain outcome. For example age on disease X.

I coded dummy variables from ordinal and nominal data (age, gender, etc) to create 2x2 tables. So, I turn my three age categories into three 2x2 tables. Lets say, I have an age category "young" vs "really old" and a "middle aged" vs "really old" and then I want to calculate the RR for each of these to test if there is an increased risk of being young vs being really old and contracting disease X as well as for being middle aged vs really old and contracting disease X.

So I ran a logistic regression (proc genmod) to get my RR's and I compared my results later with the proc freq method and my results loose statistical significance in the logistic regression because my CI are much wider. (Plus my actual RR is more extreme as well, meaning if the RR is high in log reg, then it is even higher in proc freq.)

I assume this is because each procedure uses a different calculation but I don't understand the statistics behind it well enough to understand the reaction. And which test statistic is more believable?

Thanks so much for any help!

EDIT:

here the two test statistics:

proc freq data=test;
table age_young*disease/all;
run;

vs

proc genmod data=test;
class age_young;
model disease = age_young/ dist = poisson link = log;
estimate 'Beta' age_young -1 1/ exp;
run;

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  • $\begingroup$ Could you be more specific about what is being compared to what? $\endgroup$
    – whuber
    Commented Jun 15, 2016 at 22:34
  • $\begingroup$ Comparing Age to disease: Age_young with the values: 0 & 1 compared to disease X with values: 0 & 1 Then Age_middle: 0 & 1 also with disease X. $\endgroup$
    – Catnipper
    Commented Jun 15, 2016 at 22:46
  • $\begingroup$ What I meant was, you are asking about the results of two different procedures. Since you haven't described those procedures clearly, your question is ambiguous concerning what you did, what you found, and what the differences are. That makes it difficult to understand and very difficult to answer objectively. $\endgroup$
    – whuber
    Commented Jun 15, 2016 at 22:47
  • $\begingroup$ This question is better posed on the SAS support community site. $\endgroup$
    – user78229
    Commented Jul 2, 2016 at 14:36
  • $\begingroup$ What are 'CI', 'OR' and 'RR'? Please define all abbreviations you use. $\endgroup$ Commented Jul 2, 2016 at 16:43

1 Answer 1

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"So I ran a logistic regression (proc genmod)" You didnt specify logistic model in genmod procedure but Poisson. https://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_genmod_sect022.htm It should be dist=bin link=logit.

EDIT: Or if you're not sure how to utilize GLM framework, use standard proc logistic.

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