> On Oct 22, 2017, at 3:56 PM, Sorkin, John <jsor...@som.umaryland.edu> wrote: > > David, > Thank you for responding to my post. > > Please consider the following output (typeregional is a factor having two > levels, "regional" vs. "general"): > Call: > glm(formula = events ~ type, family = poisson(link = log), data = data, > offset = log(SS)) > > Deviance Residuals: > Min 1Q Median 3Q Max > -43.606 -17.295 -4.651 4.204 38.421 > > Coefficients: > Estimate Std. Error z value Pr(>|z|) > (Intercept) -2.52830 0.01085 -233.13 <2e-16 *** > typeregional 0.33788 0.01641 20.59 <2e-16 *** > > Let's forget for a moment that the model is a Poisson regression and pretend > that the output is from a simple linear regression, e.g. from lm. > > To get the estimate for "general" one simply needs to use the value of the > intercept i.e. -2.5830. Similarly to get the 95% CI of general one simply > needs to compute -2.52830-(1.96*0.01085) and -2.52830+(1.96*0.01085). > > To get the estimate for "regional" one needs to compute intercept + > typeregional, i.e. -2.52830 + 0.33788. To get the 95% CI is somewhat more > difficult as one needs to use results from the variance-covariance matix, > specifically the variance of intercept, the variance of "regional", and the > covariance of (intercept,"regional") which involves: > var = var(intercept) + var(regional) +2*(covar(intercept,regional)), > and then get the SE of the variance > SE=sqrt(var) > 95% CI = intercept + regional - 1.95*SE and intercept + regional + 1.95*SE. > > I was hoping that a contrast statement could be written that would give me > the point estimate and SE for "general" and its SE and another contrast > statement could be written that would give me the point estimate and SE for > "general" and it SE without my having to work directly with the > variance-covariance matrix. I tried doing this using the fit.contrast > statements (from the gmodels package):
I'm guessing that the second contrast you were hoping for was actually for "regional". Contrasts, hence the name, are for differences between two levels (or more accurately between the means on the scale specified by the link parameter. In the absence of another level the only other reference point would be a value of zero or perhaps the value you specified by your offset term. -- David > > fit.contrast(model,type,c(1,0),showall=TRUE) > fit.contrast(model,type,c(0,1),showall=TRUE) > > and received the error message, > Error in `[[<-`(`*tmp*`, varname, value = c(0, 1)) : > no such index at level 1 > > Perhaps fit.contrast is not the way to accomplish my goal. Perhaps my goal > can be accomplished without a contrast statement, but I don't know how. > > Thank you, > John > > > > 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) > > > > From: David Winsemius <dwinsem...@comcast.net> > Sent: Sunday, October 22, 2017 1:20 PM > To: Sorkin, John > Cc: r-help@r-project.org > Subject: Re: [R] Syntax for fit.contrast > > > > On Oct 22, 2017, at 6:04 AM, Sorkin, John <jsor...@som.umaryland.edu> wrote: > > > > 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 > > ?fit.contrast > No documentation for ‘fit.contrast’ in specified packages and libraries: > you could try ‘??fit.contrast’ > > Perhaps the gmodels function of that name? > > > 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) > > > > I'm having trouble understanding what you are trying to extract. There are > only 2 levels so there is really only one interesting contrast ("general" vs > "regional") , and it's magnitude would be reported by just typing `model`, > and it's SE would show up in output of `summary(model)`. > > I'm thinking you should pick one of the examples in gmodels::fit.contrast > that most resembles your real problem, post it, and and then explain what > difficulties you are having with interpretation. > > -- > David. > > > > 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) > > > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > David Winsemius > Alameda, CA, USA > > 'Any technology distinguishable from magic is insufficiently advanced.' > -Gehm's Corollary to Clarke's Third Law David Winsemius Alameda, CA, USA 'Any technology distinguishable from magic is insufficiently advanced.' -Gehm's Corollary to Clarke's Third Law ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.