Hi,
I'm trying to fit a logit model to a set of data that was collected under a
split plot scheme. The structure of the data is
Whole plot factors: Watering Frequency (2 levels: Hi/Lo) and Fertilizer type (3
factors A/B/C)
Subplot factor: slope type (2 factors up/down)
Response: Proportion of infected leaves(Infected leaves/Total leaves) of the
plant (2 plants recorded from each plot)
Dataset (Partial)
Water Fert Slope Plant Total Infect
Hi A up 1 24 2
Hi A up 2 31 1
Hi A down 1 21 0
Hi A down 2 34 0
Hi ...
Hi ...
Lo
Lo
All of the factors (Whole plot and subplot) are fixed
In addition there are a lot of plants that are not affected at all, so there are
lot zeros
I'm trying to use the vglm function in VGAM package with zibinomial
distribution. I'm a little confused about how to input the covariates to
indicate a split plot design. My first try was
bmod<-vglm(cbind(Infect, Total)~Water*Fert+Slope/(Water*Fert), zibinomial,
data=FertPlots)
I would like to know if the syntax I have used in the predictors is right for
the split plot model. If not, how do I give the split plot model in R.
summary(bmod) does not give any p-values for individual tests or a degrees of
freedom to test them. How do I test these factors using the vglm function?
Thank you
Dilan Paranagama
