On Mon, 13 May 2013, meng wrote:
> Hi all:
> I have a question about poisson regression.
>
> My data:
> drug result count
> 1 1 8
> 1 2 54
> 2 1 20
> 2 2 44
>
> My model:
> model<- glm(count ~ drug*result, family = poisson)
>
> My result:
> summary(model)
>
> Coefficients:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) 2.0794 0.3536 5.882 4.06e-09 ***
> drug2 0.9163 0.4183 2.190 0.0285 *
> result2 1.9095 0.3788 5.041 4.64e-07 ***
> drug2:result2 -1.1211 0.4650 -2.411 0.0159 *
>
> Calculation of coefficients:
> Intercept: drug=1 and result=1,the corresponding count is 8.So log(8) is
2.079442 which is Intercept.
>
> My question: How is drug2 calculated? log(64)-log(62) or something like
> that(indicates the difference between drug2 and drug1) ? I've searched
> and tried many times for all possible solutions,but the result is not
> 0.9163.So,how is drug2 calculated ?
It's the drug2 effect (on a log-scale) for result=1, i.e.,
log(20) - log(8).
The four coefficients are:
R> y <- c(8, 20, 54, 44)
R> c(log(y[1]), log(y[2]) - log(y[1]), log(y[3]) - log(y[1]),
+ (log(y[4]) - log(y[3])) - (log(y[2]) - log(y[1])))
[1] 2.0794415 0.9162907 1.9095425 -1.1210851
> Many thanks!
>
>
> Best
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>
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