Sure it does, but still struggling with what is going on...

Thanks

John


________________________________
From:David Winsemius <dwinsem...@comcast.net>
To:David Winsemius <dwinsem...@comcast.net>

oject.org>
Sent:Monday, November 7, 2011 10:27 PM
Subject:Re: [R] why NA coefficients

But this output suggests there may be alligators in the swamp:

> predict(lmod, newdata=data.frame(treat=1, group=2))
         1
0.09133691
Warning message:
In predict.lm(lmod, newdata = data.frame(treat = 1, group = 2)) :
  prediction from a rank-deficient fit may be misleading

--David.
> 
> --David.
>> 
>> Thanks
>> 
>> John
>> 
>> 
>> From: David Winsemius <dwinsem...@comcast.net>

>> Cc: "r-help@r-project.org" <r-help@r-project.org>
>> Sent: Monday, November 7, 2011 5:13 PM
>> Subject: Re: [R] why NA coefficients
>> 
>> 
>> On Nov 7, 2011, at 7:33 PM, array chip wrote:
>> 
>> > Hi, I am trying to run ANOVA with an interaction term on 2 factors (treat 
>> > has 7 levels, group has 2 levels). I found the coefficient for the last 
>> > interaction term is always 0, see attached dataset and the code below:
>> >
>> >> test<-read.table("test.txt",sep='\t',header=T,row.names=NULL)
>> >> lm(y~factor(treat)*factor(group),test)
>> >
>> > Call:
>> > lm(formula = y ~ factor(treat) * factor(group), data = test)
>> >
>> > Coefficients:
>> >                  (Intercept)                factor(treat)2                
>> >factor(treat)3
>> >                      0.429244                      0.499982                
>> >      0.352971
>> >                factor(treat)4                factor(treat)5                
>> >factor(treat)6
>> >                    -0.204752                      0.142042                 
>> >     0.044155
>> >                factor(treat)7                factor(group)2  
>> >factor(treat)2:factor(group)2
>> >                    -0.007775                      -0.337907                
>> >      -0.208734
>> > factor(treat)3:factor(group)2  factor(treat)4:factor(group)2  
>> > factor(treat)5:factor(group)2
>> >                    -0.195138                      0.800029                 
>> >     0.227514
>> > factor(treat)6:factor(group)2  factor(treat)7:factor(group)2
>> >                      0.331548                            NA
>> >
>> >
>> > I guess this is due to model matrix being singular or collinearity among 
>> > the matrix columns? But I can't figure out how the matrix is singular in 
>> > this case? Can someone show me why this is the case?
>> 
>> Because you have no cases in one of the crossed categories.
>> 
>> --David Winsemius, MD
>> West Hartford, CT
>> 
>> 
>> 
> 
> David Winsemius, MD
> West Hartford, CT
> 
> ______________________________________________
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David Winsemius, MD
West Hartford, CT
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