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 <dwinsemius at comcast.net>
Sent: Sunday, October 22, 2017 1:20 PM
To: Sorkin, John
Cc: r-help at r-project.org
Subject: Re: [R] Syntax for fit.contrast
> On Oct 22, 2017, at 6:04 AM, Sorkin, John <jsorkin at
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 at r-project.org mailing list -- To UNSUBSCRIBE and more, see
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> 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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