Hi ! how to perform anova on binomial response data using glm procedure,
could anyone help us with this problem ? we are trying to test the a
model of binomial response with non-ordered categorical factors. I am
not getting the significance of each factors but, the departure from the
binomial model within each category.
For example : Two factors, A and B, one binomial matrix response Ymat
I want to get the effect of F1, F2, F1*F2
If I test the model Ymat ~ F1*F2, with glm :
fml <- glm(Ymat ~ F1*F2, family = binomial(link=probit), data = data.df)
summary(fml)
I get levels of significance within each level of the different factors
and all their interactions, I cannot figure out how to get the effect of
the factors themselves and their interaction on the binomial response.
something like that:
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.21972 0.18642 1.179 0.23854
F1b 0.16444 0.22118 0.743 0.45719
F1c -0.06241 0.24396 -0.256 0.79809
F1d 0.16560 0.23554 0.703 0.48203
F1e 0.11228 0.21025 0.534 0.59331
F2b -0.02052 0.34442 -0.060 0.95249
F2c 0.27298 0.27000 1.011 0.31200
F2d 0.21100 0.32371 0.652 0.51451
F2e 0.97407 0.31176 3.124 0.00178 **
F2f 0.25457 0.23411 1.087 0.27687
F1b:F2b 0.15497 0.38003 0.408 0.68343
F1c:F2b 0.22932 0.42740 0.537 0.59158
F1d:F2b 0.43980 0.40695 1.081 0.27982
F1e:F2b 0.46955 0.39571 1.187 0.23539
F1b:F2c -0.17764 0.36336 -0.489 0.62492
F1c:F2c 0.43913 0.42142 1.042 0.29740
F1d:F2c -0.09235 0.58819 -0.157 0.87524
etc...
do you how can I get the effect of the factors themselves, not the
departure from binomial model within each catagory ?
Thanks for your help,
St?phane
--
St?phane DUPAS
IRD c/o CNRS
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