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Sorkin, John

2017-Oct-22 22:56 UTC

[R] Syntax for fit.contrast (from package gmodels)

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
> 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

	[[alternative HTML version deleted]]

David Winsemius

2017-Oct-22 23:56 UTC

head link

[R] Syntax for fit.contrast (from package gmodels)

> On Oct 22, 2017, at 3:56 PM, Sorkin, John <jsorkin at
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 <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
> > 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

Sorkin, John

2017-Oct-23 00:01 UTC

head link

[R] Syntax for fit.contrast (from package gmodels)

David,

Again  you have my thanks!.

You are correct. What I want is not technically a contrast. What I want is the
estimate for "regional" and its SE. I don't mind if I get these on
the log scale; I can get the anti-log. Can you suggest  how I can get the point
estimate and its SE for "regional"? The predict function will give the
point estimate, but not (to my knowledge) the SE.

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 7:56 PM
To: Sorkin, John
Cc: r-help at r-project.org
Subject: Re: [R] Syntax for fit.contrast (from package gmodels)

> On Oct 22, 2017, at 3:56 PM, Sorkin, John <jsorkin at
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 <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
> > 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






	[[alternative HTML version deleted]]

Martin Maechler

2017-Oct-23 08:10 UTC

head link

[R] Syntax for fit.contrast (from package gmodels)

>>>>> Sorkin, John <jsorkin at som.umaryland.edu>
>>>>>     on Sun, 22 Oct 2017 22:56:16 +0000 writes:
    > 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).

I'm pretty sure you can just use  (the base R) functions

  dummy.coef()

or
  model.tables()

possibly with SE=TRUE to get coefficients for all levels of a factor..
I'd like to have tried to show this here, but for that we'd have
wanted to see a "MRE" or "ReprEx" (minimal reproducible
example) ..

    > 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.

My guess is that "standard R" aka "base R" would be
sufficient to get what you'd want, notably if you'd consider
using  se.contrast() additionally.

Martin


    > Thank you,
    > John

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