R help - Jul 2010 - Transformation of Y changes the 'lm' object?

Hi R,

 

This is a problem, which I have tried to present in a simple way:

 

Let,

 

x1=1:10

x2=2:11

y=2+3*x1

lm_obj=lm(y~x1+x2)

lm_obj

step(lm_obj) # Step function for the first time

 

 

y=y^0.1

lm_obj

step(lm_obj) #Step function after a transformation on Y, but 'lm_obj' is
not modified.

 

 

 

The two step function behave differently. The first one is before the
transformation on 'Y', the dependent variable and the second step
function is after the transformation. But, please note that I have NOT changed
the 'lm_obj' at all after the transformation at all. So, I was
wondering, since I have not changed the 'lm_obj', I should get both
stepwise results as the same. Or does the transformation of Y, changes the
'lm_obj' without actually specifying?

 

Thanks for the clarifications.

 

 

Thanks and Regards,

Shubha Karanth | Amba Research

Ph +91 80 3980 8435 | Mob +91 94 4886 4510

Bangalore * Colombo * London * New York * San José * Singapore *
www.ambaresearch.com

 

 

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On Tue, 2010-07-20 at 13:16 +0530, Shubha Vishwanath Karanth
wrote:
> Hi R,
> 
>  
> 
> This is a problem, which I have tried to present in a simple way:
> 
>  
> 
> Let,
> x1=1:10
> 
> x2=2:11
> 
> y=2+3*x1
> 
> lm_obj=lm(y~x1+x2)
> 
> lm_obj
> 
> step(lm_obj) # Step function for the first time
> y=y^0.1
> 
> lm_obj
> 
> step(lm_obj) #Step function after a transformation on Y, but
'lm_obj'
> is not modified.
You didn't modify lm_obj so it can't change.
> The two step function behave differently. The first one is before the
> transformation on 'Y', the dependent variable and the second step
> function is after the transformation. But, please note that I have NOT
> changed the 'lm_obj' at all after the transformation at all. So, I
was
> wondering, since I have not changed the 'lm_obj', I should get both
> stepwise results as the same. Or does the transformation of Y, changes
> the 'lm_obj' without actually specifying?
I don't know exactly why step changes, but it is because your variables
are in the workspace not an explicitly defined object. Step update()s
the model fitted in lm_obj. As you told it (implicitly) to look in the
workspace for y, x1, x2 and changed y between the two runs of step it
does not surprise me that the results changed. Why this happens probably
has something to do with environments attached to the model formula or
terms object of the fitted model, but I don't know the specifics of this
to venture further explanation.

You can avoid this by putting your data into a data frame prior to model
fitting.

x1 <- 1:10
x2 <- 2:11
y <- 2 + 3 * x1
d <- data.frame(x1 = x1, x2 = x2, y = y)
lmObj <- lm(y ~ x1 + x2)
lmObj2 <- lm(y ~ x1 + x2, data = d)
lmObj
lmObj2

## step them
step(lmObj)
step(lmObj2)

## modify y
y <- y^0.1

## step them again
step(lmObj)  ## this changes as you observed
step(lmObj2) ## this doesn't change

HTH

G

Ps; I find it interesting, and slightly perverse, that you space your
individual lines of code out with repeated carriage returns but squash
the code *within* lines up allowing no whitespace. That really doesn't
help readability.

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