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):


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






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