# [R] Help - lm, glm, aov results inconsistent with other stati stical package

Prof Brian Ripley ripley at stats.ox.ac.uk
Wed Mar 1 08:55:54 CET 2006

```I think we should clarify your subject line.  >One< other statistical
package (JMP) is giving in your hands results inconsistent with R.

I have to say I am puzzled by this.  Why ask the volunteers here why you
get a different result in JMP from the answer given by R?  You could ask
your support contact for JMP, where there will be people whom you have
paid to answer your question.  (People here are not going to be very
interested in the reliability of JMP.)

On Tue, 28 Feb 2006, Ben Ridenhour wrote:

> Alright, I'll try to give some sample code.
>
> # create A with 2 levels - 2 and 4
> > A<-c(rep(2,times=30),rep(4,times=42))
>
> # make A a factor
> > A<-as.factor(A)
>
>   #generate 72 random x points
> > x<-rnorm(72)
>
>  #create different slopes & intercepts for A=2 and A=4
> #add a random error term
> > y<-c(x[(1:30)]+1,2*x[(31:72)]-2)+rnorm(72,mean=0,sd=2)
>
> #use model y~A*x for lm (or glm)
> > test.lm<-lm(y~A*x)
>
> #check the output
> > summary(test.lm)
>
> This essentially creates something like my data set and uses the same
> model.  In response to (1), I was just using 0/1 because these are
> codings for the 2 levels, correct? (i.e., when A=2 the dummy variable=0,
> when A=4 the dummy variable=1?).  In response to (2), yes, I do want
> different slopes for the two categories (that is what I am interested in
> testing).
>
> If I export the data created above to JMP and run what I believe to be
> the same model, I get a different answer for my equations :(
>
>
> -------------------------------
> Benjamin Ridenhour
> School of Biological Sciences
> Washigton State University
> P.O. Box 644236
> Pullman, WA 99164-4236
> Phone (509)335-7218
> --------------------------------
> "Nothing in biology makes sense except in the light of evolution."
> -T. Dobzhansky
>
>
> ----- Original Message ----
> From: "Liaw, Andy" <andy_liaw at merck.com>
>
> Sent: Tuesday, February 28, 2006 5:14:57 PM
> Subject: RE: [R] Help - lm, glm, aov results inconsistent with other stati stical package
>
> 1. You have levels(A) as "2" and "4", yet you showed equations for A=0 and
> A=1?
>
> 2. y = A + X + A*X means you're allowing the different groups of A to have
> different slopes.  Probably not what you intended.
>
> 3. It's probably best to provide a small sample of the data (and R code) so
> we know how you got what you got.
>
> Andy
>
> From: Ben Ridenhour
>>
>> Hello,
>>
>>  I 'm sure there must a be a simple explanation for what I'm
>> doing wrong but I am stumped.  I am a novice R user and this
>> has shaken my confidence in what I'm doing! I am trying to
>> run a simple ANCOVA using the model y~A*x, where y and x are
>> continuous and A has two levels.  Everything seems fine until
>> I compare the output with what I get from another statistical
>> package (JMP).  JMP has the model y=A+x+A*x (this should be
>> the same as what I specified to R, correct?).  In comparison
>> I get the line equations
>>
>>  y = 7072.09-1024.94 x (for A=0) and
>>  y = 7875.58-970.088 x (for A=1)
>>
>>  from JMP.  And from R I get
>>
>>  y = 6276.7-1259.8 x (for A=0) and
>>  y = 7867.5-1150.1 x (for A=1).
>>
>>  Obviously, these aren't even close to the same answer.  I've
>> tried this using glm(), lm(), and aov() and as expected they
>> all give the same answer.  If I do
>>
>> >levels(A)
>>  [1] "2" "4"
>>
>>  which are the two levels of A.  Why can't I get the same
>> answer from JMP as in R?  This is very disturbing to me!
>>
>>  Thanks,
>>  Ben
>>
>>
>> -------------------------------
>> Benjamin Ridenhour
>> School of Biological Sciences
>> Washigton State University
>> P.O. Box 644236
>> Pullman, WA 99164-4236
>> Phone (509)335-7218
>> --------------------------------
>> "Nothing in biology makes sense except in the light of evolution."
>> -T. Dobzhansky
>>
>>
>>
>>     [[alternative HTML version deleted]]
>>
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>>
>>
>
>
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--
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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