Getting vastly different results when running GLMs

Hi Luke,

The differences you are seeing are almost certainly due to different
contrast codings: Statistica probably uses sum-to-zero contrasts whereas R
uses treatment (Dunnett) contrasts by default. You would be well advised to
consult a local statistician for a deeper understanding.

For some immediate insight do the following:

## Fits your model with different contrasts + a few other things.
##
library(car)
?contrast
?contr.treatment
model1 <- glm((cbind(spec,total)) ~ behav * loc, family=binomial,
data=behdata, contrasts=list(behav="contr.treatment",
loc="contr.treatment"))
model2 <- glm((cbind(spec,total)) ~ behav * loc, family=binomial,
data=behdata, contrasts=list(behav="contr.sum", loc="contr.sum"))

summary(model1)
summary(model2)
anova(model1, model2)      ## see: models seem different but are identical

## Type I SS
anova(model1)
anova(model2)

## Type II SS
library(car)
Anova(model1, type="II")
Anova(model2, type="II")

Regards, Mark.

-----
Mark Difford (Ph.D.)
Research Associate
Botany Department
Nelson Mandela Metropolitan University
Port Elizabeth, South Africa
--
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