[R] why NA coefficients

[David Winsemius]

On Nov 8, 2011, at 1:19 AM, David Winsemius wrote:

>
> On Nov 7, 2011, at 10:07 PM, array chip wrote:
>
>> Thanks David. The only category that has no cases is "treat 1-group  
>> 2":
>>
>> > with(test,table(treat,group))
>>     group
>> treat 1 2
>>    1 8 0
>>    2 1 5
>>    3 5 5
>>    4 7 3
>>    5 7 4
>>    6 3 3
>>    7 8 2
>>
>> But why the coefficient for "treat 7-group 2" is not estimable?
>
> Well, it had to omit one of them didn't it?
>
> (But I don't know why that level was chosen.)

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 <dwinsemius at comcast.net>
>> To: array chip <arrayprofile at yahoo.com>
>> Cc: "r-help at r-project.org" <r-help at 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