In R using:
formula = (ENF/TOT) ~ (VAR1 + VAR2 + VAR3 + VAR4)^2 would give you all
the main effects and 2 way interactions.
What do you mean by the R^2 for a binary model? It is not constructed
simply by minimizing the squared distances from the 0,1 outcomes.
There are analogues to R^2 (and one notorious software package offers
one without adequate explanation of what it means), but the fact that
you are asking the question suggests you need to crack open your
texts. You need to focus on the difference in deviance when working
with generalized linear models.
--
David Winsemius
On Feb 7, 2009, at 9:13 AM, Alberto Maceda wrote:
Hello R-users,
My first consult is that I would like to tackle the relationship
between a
dependent variable and four environmental factors using a glm binomial
model. The problem is that I want to test the interaction between
factors
too and I would like to learn some way to do it automatically.
Now, my syntax is, for instance:
E1<-glm(formula = (ENF/TOT)~VAR1+VAR2+VAR3+VAR4, family = binomial,
data =
DATA, weights = TOT)
And I would like to add pair interactions at least:
VAR1*VAR2+VAR1*VAR3,
etc... for all possible combinations.
My second question is that the model does not show me the R-squared
neither
using summary(E1) nor writing simply E1.
Thank you very much!
[[alternative HTML version deleted]]
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