I have a model (run with glm) that has a factor, type. Type has two levels,
"general" and "regional". I am trying to get estimates (and SEs) for the model
with type="general" and type ="regional" using fit.contrast but I can't get the
syntax of the coefficients to use in fit.contrast correct. I hope someone can
show me how to use fit.contrast, or some other method to get estimate with SEs.
(I know I can use the variance co-variance matrix, but I would rather not have
to code the linear contrast my self from the coefficients of the matrix)
Thank you,
John
My model:
model=glm(events~type,family=poisson(link=log),offset=log(SS),data=data)
Model details:
> summary(data$type)
general regional
16 16
> levels(data$type)
[1] "general" "regional"
> contrasts(data$type)
regional
general 0
regional 1
I have tried the following syntax for fit.contrast
fit.contrast(model,type,c(1,0))
and get an error:
Error in `[[<-`(`*tmp*`, varname, value = cmat) :
no such index at level 1
> fit.contrast(model,type,c(0,1),showall=TRUE)
and get an error:
Error in `[[<-`(`*tmp*`, varname, value = cmat) :
no such index at level 1
> fit.contrast(model,type,c(1,-1),showall=TRUE)
and get an error:
Error in `[[<-`(`*tmp*`, varname, value = cmat) :
no such index at level 1
> fit.contrast(model,type,c(0))
and get an error:
Error in make.contrasts(coeff, ncol(coeff)) :
Too many contrasts specified. Must be less than the number of factor levels
(columns).
> fit.contrast(model,type,c(1))
Error in make.contrasts(coeff, ncol(coeff)) :
and get an error
Too many contrasts specified. Must be less than the number of factor levels
(columns).
John David Sorkin M.D., Ph.D.
Professor of Medicine
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology and Geriatric
Medicine
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
(Phone) 410-605-7119
(Fax) 410-605-7913 (Please call phone number above prior to faxing)
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