Re: [R] Question on partial effect

From: Guo Wei-Wei <wwguocn_at_gmail.com>
Date: Wed 12 Jul 2006 - 11:37:06 EST

Than you, Gavin. You helped me out a lot of problems.

Thank you very much!
Wei-Wei

2006/7/12, Gavin Simpson <gavin.simpson@ucl.ac.uk>:
> On Wed, 2006-07-12 at 00:51 +0800, Guo Wei-Wei wrote:
> > Thank you, Gavin. I think that might be what I need. But I'm a little
> > bit wandering what's the scale of resid(mod). Is it
> > scale(dist)/scale(speed), for example kilometer / (kilometer per
> > hour)? or something else?
> >
> > Thank you very much!
> > Wei-Wei
>
> The scale of dist - they are just the differences between observed dist
> and fitted dist (based on speed).
>
> mod <- lm(dist ~ speed, data = cars)
> resid(mod)
>
> 1 2 3 4 5
> 3.849460 11.849460 -5.947766 12.052234 2.119825
> 6 7 8 9 10
> -7.812584 -3.744993 4.255007 12.255007 -8.677401
> ....
>
> # visualise the residuals
> plot(resid(mod) ~ dist, data = cars)
> abline(h = 0, col = "grey")
> ## length of blue line represents the residual
> lines(cars$dist, resid(mod), type = "h", col = "blue")
>
> So you see that for the 1st residual it is 3.849 ft (the distances are
> measured in feet, see ?cars)
>
> Does this help?
>
> G
>
> >
> >
> > 2006/7/12, Gavin Simpson <gavin.simpson@ucl.ac.uk>:
> > > On Tue, 2006-07-11 at 23:51 +0800, Guo Wei-Wei wrote:
> > > > Dear all,
> > > >
> > > > I don't know what's my question is called. I have a performance
> > > > variable A, such as sales. And I have another variable B, let's say
> > > > establish time of firm. I want to create the third variable that is
> > > > sales without the effect of establish time. Maybe it can be called
> > > > partial effect problem. I'm not sure.
> > > >
> > > > Does anyone have any suggestion? Thank you in advance!
> > > >
> > > > All the best,
> > > > Wei-Wei
> > >
> > > Do you mean?
> > >
> > > ## dummy data
> > > A <- rnorm(100)
> > > B <- rnorm(100)
> > > C <- resid(lm(A ~ B))
> > >
> > > C now contains the residual variation in A after fitting B.
> > >
> > > e.g. with some real data
> > > ?cars
> > > data(cars) # not sure this is needed now, I forget
> > > mod <- lm(dist ~ speed, data = cars)
> > > summary(mod)
> > > partial <- resid(mod)
> > >
> > > ## check
> > > mod2 <- lm(dist ~ partial, data = cars)
> > > summary(mod2)
> > > ## from the two R^2 form mod1 and mod2 - partial contains dist minus
> > > ## the effects of speed
> > > > 0.6511 + 0.3489
> > > [1] 1
> > >
> > > HTH
> > >
> > > G
> > > --
> > > %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
> > > Gavin Simpson [t] +44 (0)20 7679 0522
> > > ECRC & ENSIS, UCL Geography, [f] +44 (0)20 7679 0565
> > > Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk
> > > Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/cv/
> > > London, UK. WC1E 6BT. [w] http://www.ucl.ac.uk/~ucfagls/
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> > >
> > >
> >
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> Gavin Simpson [t] +44 (0)20 7679 0522
> ECRC & ENSIS, UCL Geography, [f] +44 (0)20 7679 0565
> Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk
> Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/cv/
> London, UK. WC1E 6BT. [w] http://www.ucl.ac.uk/~ucfagls/
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