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Posted 04-09-2020 11:05 PM
(1268 views)

Hi everyone,

I am really struggling with the analysis of equality of variance as one of the assumptions of Poisson regression.

Here is what I am doing:

```
proc glimmix data=have;
by group;
class disease sex;
effect yearspline=spline(year / naturalcubic knotmethod=equal(5));
effect agespline=spline(age / naturalcubic knotmethod=equal(5));
model events=disease sex aspl yspl / dist=poisson offset=logtime s cl link=log;
random _residual_/group=disease;
covtest homogeneity;
run;
```

I am doing the right thing with covtest?

The result of 'test of covariance parameters based on residual pseudo likelihhod' is coming with a Homogeneity p value of <0.0001. Does that mean that there is significant difference in the variance between the 'disease' groups and that the quality of variance assumption for poisson regression is not met, and hence I should not be using this Poisson model?

Thanks

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Thank you @StatDave you are absolutely correct, my bad, i should have siad 'equality of variance and mean'.

So what i am actually trying to do is to test the assumption that the mean and variance are equal in my data/model...

Any suggestions/thoughts on how to do that and if my code up is right?

Thank you

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