R help - Oct 2011 - Contrasts with an interaction. How does one specify the dummy variables for the interaction

Forgive my resending this post. To data I have received only one response (thank
you Bert Gunter), and I still do not have an answer to my question.
Respectfully,
John


Windows XP
R 2.12.1
contrast package.


I am trying to understand how to create contrasts for a model that contatains an
interaction. I can get contrasts to work for a model without interaction, but
not after adding the interaction. Please see code below. The last two contrast
statements show the problem. I would appreciate someone letting me know what is
wrong with the syntax of my contrast statements.
Thank you,
John


library(contrast)

# Create 2x2 contingency table.
counts=c(50,50,30,70)
row <-    gl(2,2,4)
column <- gl(2,1,4)
mydata <- data.frame(row,column,counts)
print(mydata)

# Show levels of 2x2 table
levels(mydata$row)
levels(mydata$column)


# Models, no interaction, and interaction
fitglm0 <- glm(counts ~ row + column,             
family=poisson(link="log"))
fitglm  <- glm(counts ~ row + column + row*column,
family=poisson(link="log"))

# Contrasts for model without interaction works fine!
anova(fitglm0)
summary(fitglm0)
con0<-contrast(fitglm0,list(row="1",column="1"))
print(con0,X=TRUE)

# Contrast for model with interaction does not work.
anova(fitglm)
summary(fitglm)
con<-contrast(fitglm,list(row="1",column="1")
print(con,X=TRUE)

# Nor does this work.
con<-contrast(fitglm,list(row="1",column="1",row:column=c("0","0")))
print(con,X=TRUE)




John David Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology
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)

Confidentiality Statement:
This email message, including any attachments, is for th...{{dropped:6}}

Is there a specific reason why you insist on using the contrast library? If
not:

# Create 2x2 contingency table.
counts=c(50,50,30,70)
row <-    gl(2,2,4)
column <- gl(2,1,4)
mydata <- data.frame(row,column,counts)
print(mydata)

#Create contrasts

row<-factor(row)
column<-factor(column)
contrasts(row)<-contr.treatment(levels(row))
contrasts(column)<-contr.treatment(levels(column))

# Works for Terps

fit.terp<-glm(counts ~ row + column + row*column,
family=poisson(link="log"))
summary(fit.terp)

HTH,

Daniel Malter
University of Maryland, College Park





John Sorkin wrote:
> 
> Forgive my resending this post. To data I have received only one response
> (thank you Bert Gunter), and I still do not have an answer to my question.
> Respectfully,
> John
> 
> 
> Windows XP
> R 2.12.1
> contrast package.
> 
> 
> I am trying to understand how to create contrasts for a model that
> contatains an interaction. I can get contrasts to work for a model without
> interaction, but not after adding the interaction. Please see code below.
> The last two contrast statements show the problem. I would appreciate
> someone letting me know what is wrong with the syntax of my contrast
> statements.
> Thank you,
> John
> 
> 
> library(contrast)
> 
> # Create 2x2 contingency table.
> counts=c(50,50,30,70)
> row <-    gl(2,2,4)
> column <- gl(2,1,4)
> mydata <- data.frame(row,column,counts)
> print(mydata)
> 
> # Show levels of 2x2 table
> levels(mydata$row)
> levels(mydata$column)
> 
> 
> # Models, no interaction, and interaction
> fitglm0 <- glm(counts ~ row + column,             
> family=poisson(link="log"))
> fitglm  <- glm(counts ~ row + column + row*column,
> family=poisson(link="log"))
> 
> # Contrasts for model without interaction works fine!
> anova(fitglm0)
> summary(fitglm0)
> con0<-contrast(fitglm0,list(row="1",column="1"))
> print(con0,X=TRUE)
> 
> # Contrast for model with interaction does not work.
> anova(fitglm)
> summary(fitglm)
> con<-contrast(fitglm,list(row="1",column="1")
> print(con,X=TRUE)
> 
> # Nor does this work.
>
con<-contrast(fitglm,list(row="1",column="1",row:column=c("0","0")))
> print(con,X=TRUE)
> 
> 
> 
> 
> John David Sorkin M.D., Ph.D.
> Chief, Biostatistics and Informatics
> University of Maryland School of Medicine Division of Gerontology
> 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)
> 
> Confidentiality Statement:
> This email message, including any attachments, is for th...{{dropped:6}}
> 
> ______________________________________________
> R-help@ mailing list
> 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.
> 

--
View this message in context:
http://r.789695.n4.nabble.com/Contrasts-with-an-interaction-How-does-one-specify-the-dummy-variables-for-the-interaction-tp3948792p3949071.html
Sent from the R help mailing list archive at Nabble.com.

Daniel,
I want to use the contrast library because I want to be able to specify any
arbitrary post-hoc contrast, e.g. Given a 3x2 table describing smoking (never,
former, current) by sex (male,female), I can use a post-hoc contrast to compare
the fraction of female former smokers to the fraction of male former smokers, or
the fraction of male former smokers to the fraction of male current smokers,
etc. To the best of my knowledge, post-hoc contrasts are the most flexible, and
easiest way to specify arbitrary pre-specified comparisons.
John

John David Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology
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)
>>> Daniel Malter <daniel at umd.edu> 10/28/2011 4:02 PM
>>>
Is there a specific reason why you insist on using the contrast library? If
not:

# Create 2x2 contingency table.
counts=c(50,50,30,70)
row <-    gl(2,2,4)
column <- gl(2,1,4)
mydata <- data.frame(row,column,counts)
print(mydata)

#Create contrasts

row<-factor(row)
column<-factor(column)
contrasts(row)<-contr.treatment(levels(row))
contrasts(column)<-contr.treatment(levels(column))

# Works for Terps

fit.terp<-glm(counts ~ row + column + row*column,
family=poisson(link="log"))
summary(fit.terp)

HTH,

Daniel Malter
University of Maryland, College Park





John Sorkin wrote:
> 
> Forgive my resending this post. To data I have received only one response
> (thank you Bert Gunter), and I still do not have an answer to my question.
> Respectfully,
> John
> 
> 
> Windows XP
> R 2.12.1
> contrast package.
> 
> 
> I am trying to understand how to create contrasts for a model that
> contatains an interaction. I can get contrasts to work for a model without
> interaction, but not after adding the interaction. Please see code below.
> The last two contrast statements show the problem. I would appreciate
> someone letting me know what is wrong with the syntax of my contrast
> statements.
> Thank you,
> John
> 
> 
> library(contrast)
> 
> # Create 2x2 contingency table.
> counts=c(50,50,30,70)
> row <-    gl(2,2,4)
> column <- gl(2,1,4)
> mydata <- data.frame(row,column,counts)
> print(mydata)
> 
> # Show levels of 2x2 table
> levels(mydata$row)
> levels(mydata$column)
> 
> 
> # Models, no interaction, and interaction
> fitglm0 <- glm(counts ~ row + column,             
> family=poisson(link="log"))
> fitglm  <- glm(counts ~ row + column + row*column,
> family=poisson(link="log"))
> 
> # Contrasts for model without interaction works fine!
> anova(fitglm0)
> summary(fitglm0)
> con0<-contrast(fitglm0,list(row="1",column="1"))
> print(con0,X=TRUE)
> 
> # Contrast for model with interaction does not work.
> anova(fitglm)
> summary(fitglm)
> con<-contrast(fitglm,list(row="1",column="1")
> print(con,X=TRUE)
> 
> # Nor does this work.
>
con<-contrast(fitglm,list(row="1",column="1",row:column=c("0","0")))
> print(con,X=TRUE)
> 
> 
> 
> 
> John David Sorkin M.D., Ph.D.
> Chief, Biostatistics and Informatics
> University of Maryland School of Medicine Division of Gerontology
> 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)
> 
> Confidentiality Statement:
> This email message, including any attachments, is for ...{{dropped:31}}

John,

There is a good example of one way of doing this in
"multcomp-examples.pdf"
of package multcomp. See pages 8 to 10.

Regards, Mark.

-----
Mark Difford (Ph.D.)
Research Associate
Botany Department
Nelson Mandela Metropolitan University
Port Elizabeth, South Africa
--
View this message in context:
http://r.789695.n4.nabble.com/Contrasts-with-an-interaction-How-does-one-specify-the-dummy-variables-for-the-interaction-tp3948792p3950225.html
Sent from the R help mailing list archive at Nabble.com.

This is failing because it is a saturated model and the contrast
package tries to do a t-test (instead of a z test). I can add code to
do this, but it will take a few days.

Max

On Fri, Oct 28, 2011 at 2:16 PM, John Sorkin
<JSorkin at grecc.umaryland.edu> wrote:
> Forgive my resending this post. To data I have received only one response
(thank you Bert Gunter), and I still do not have an answer to my question.
> Respectfully,
> John
>
>
> Windows XP
> R 2.12.1
> contrast package.
>
>
> I am trying to understand how to create contrasts for a model that
contatains an interaction. I can get contrasts to work for a model without
interaction, but not after adding the interaction. Please see code below. The
last two contrast statements show the problem. I would appreciate someone
letting me know what is wrong with the syntax of my contrast statements.
> Thank you,
> John
>
>
> library(contrast)
>
> # Create 2x2 contingency table.
> counts=c(50,50,30,70)
> row <- ? ?gl(2,2,4)
> column <- gl(2,1,4)
> mydata <- data.frame(row,column,counts)
> print(mydata)
>
> # Show levels of 2x2 table
> levels(mydata$row)
> levels(mydata$column)
>
>
> # Models, no interaction, and interaction
> fitglm0 <- glm(counts ~ row + column, ? ? ? ? ? ?
?family=poisson(link="log"))
> fitglm ?<- glm(counts ~ row + column + row*column,
family=poisson(link="log"))
>
> # Contrasts for model without interaction works fine!
> anova(fitglm0)
> summary(fitglm0)
> con0<-contrast(fitglm0,list(row="1",column="1"))
> print(con0,X=TRUE)
>
> # Contrast for model with interaction does not work.
> anova(fitglm)
> summary(fitglm)
> con<-contrast(fitglm,list(row="1",column="1")
> print(con,X=TRUE)
>
> # Nor does this work.
>
con<-contrast(fitglm,list(row="1",column="1",row:column=c("0","0")))
> print(con,X=TRUE)
>
>
>
>
> John David Sorkin M.D., Ph.D.
> Chief, Biostatistics and Informatics
> University of Maryland School of Medicine Division of Gerontology
> 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)
>
> Confidentiality Statement:
> This email message, including any attachments, is for ...{{dropped:16}}