Hey,

Whenever I set up a log linear model using glm(Y~. , data=data,
family=poisson) I get the parameters in the form of deviation from the first
cell kombination.

I find this to be hard to interpret when I for instance want to know if
there is a difference between two factors in the first category since those
parameters are not shown directly.
Is there any way to get the summary() command, or equivalent, to show me all
of the parameters in the model in non-deviation form?

I can use loglin() to get the parameters, but it doesnt show significance of
the parameters from what I can tell.

Alternatively, can anyone give a brief explanation of how to interpret the
model in deviation form? For example here I have the factors "Gamla" and
"Nya" and the categories "0", "1-10", "11-50", "51-100" and "101+"
The interpretation of the shown interaction terms are no problem, but how do
I figure if there is a difference between Gamla and Nya when it comes to
category "0"?

(Intercept)            7.74760    0.02078 372.852  < 2e-16 ***
typNya                -2.34943    0.07040 -33.371  < 2e-16 ***
kategori1-10          -1.88966    0.05735 -32.950  < 2e-16 ***
kategori101+          -4.05872    0.15947 -25.451  < 2e-16 ***
kategori11-50         -2.63561    0.08035 -32.802  < 2e-16 ***
kategori51-100        -4.61210    0.20955 -22.010  < 2e-16 ***
typNya:kategori1-10    0.72561    0.14935   4.858 1.18e-06 ***
typNya:kategori101+   -1.33945    1.01486  -1.320    0.187
typNya:kategori11-50   0.18189    0.25221   0.721    0.471
typNya:kategori51-100 -0.09291    0.74056  -0.125    0.900


Thanks for any help, and sorry for the supposedly basic question!
Chris

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