SAS Support Communities

Is the correct interpretation of PROC GENMOD with a poisson distribution an odds ratio such as in logistic regression, or is the interpretation the same as an OLS Parameter Estimate? ... View more

What exactly does it mean when an effect for a variable is a linear combination of other effects? I understand that it's crucial to have an omitted reference dummy, but I don't understand why in a math sense. In a regression framework, an omitted reference is necessary so that comparisons can be made on the other dummies to that reference. But why would failing to have a reference group result in a "linear combination of other effects?" I guess I need some example or plain language here if possible.  ... View more

Thank you very much, this SAS documentation is helpful. I should have mentioned that many of the subjects are not the same from year to year because of new students who enter the school and students who graduate. Given that the measures repeat, but the subjects differ, would I still need to do the interrupted time series analysis?  ... View more

Yes, will do. Thank you ... View more

Hi, I have a study in which the program (RJ) has 4 years of treatment and one pre-treatment year (exposure; coded as 0-4). I want to compare the odds of getting suspended (1/0) for students during the pre-treatment year, and each subsequent year of exposure to the RJ program with the odds of getting suspended for students who didn't receive the treatment (RJ=0).   In other words, Students exposed to treatment compared with their pre-treatment year.  Students not exposed to treatment compared with their pre-treatment year.  Students exposed compared with students not exposed.    I'm wondering what the difference would be if I use the following two codes:   PROC LOGISTIC data=studentsample;         class RJ(ref='0') exposure(ref='0')  / param=glm;         model suspended(event="1") = RJ exposure RJ*exposure;         estimate "Diff in Diff" RJ*exposure1 -1 -1 1;         lsmeans  RJ*exposure/ e ilink;         ods output coef=coeffs;         lsmestimate RJ*exposure "Diff in Diff LogOdds" 1 -1 -1 1;         store log; RUN;   versus:    PROC LOGISTIC data=studentsample descending;        class RJ (ref='0') / param=ref;        class exposure (ref='0') / param=ref; model SUSPENDED =        RJ exposure exposure*RJ        / clodds=wald ORPVALUE;        oddsratio RJ / diff=ref;        oddsratio exposure / diff=ref; RUN;   I have less familiarity in interpreting the difference-in-difference output. My understanding is that my 2nd code -- the proc logistic without the difference-in-difference specification -- still technically gives me a difference-in-difference odds ratio because I get an estimate for RJ*0 RJ*1 RJ*2 RJ*3 RJ*4, and therefore it is not necessary to specify diff-in-diff as I did in the first code. Is this not true?    I assume I'm wrong because when I run the 2nd batch of code, I get this note in the log:  : Under full-rank parameterizations, Type 3 effect tests are replaced by joint tests. The joint test for an effect is a test that all the parameters associated with that effect are zero. Such joint tests might not be equivalent to Type 3 effect tests under GLM parameterization.   Thank you ... View more

Thank you so much, yes that makes total sense. ... View more

Thank you! This is very helpful. If I were presenting results to a non-technical audience in which I couldn't use the relative risk language, would I be able to use the language "have an odds of..." instead? ... View more

Thank you for this. I am wondering how to compare the odds ratios interaction terms. For example, in the output attached by the user who wrote in, the first odds ratio is for Black where Young=0, and Male=0, with the odds being 1.336. So we can say that Black non-young, non-male persons are 1.336 times more likely to [whatever the dependent variable is]. But my question is: who are we comparing the Black non-young, non-male to? Is this compared to White non-young, non-male? Or, compared to Black, young, male? ... View more