Great. Thank you!

On Tue, May 29, 2012 at 8:11 AM, ONKELINX, Thierry <Thierry.ONKELINX@inbo.be
> wrote:

> offset() fixes the parameter to 1. So offset(I(.5*X2)) should do the trick.
>
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
> Forest
> team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
> Kliniekstraat 25
> 1070 Anderlecht
> Belgium
> + 32 2 525 02 51
> + 32 54 43 61 85
> Thierry.Onkelinx@inbo.be
> www.inbo.be
>
> To call in the statistician after the experiment is done may be no more
> than asking him to perform a post-mortem examination: he may be able to say
> what the experiment died of.
> ~ Sir Ronald Aylmer Fisher
>
> The plural of anecdote is not data.
> ~ Roger Brinner
>
> The combination of some data and an aching desire for an answer does not
> ensure that a reasonable answer can be extracted from a given body of data.
> ~ John Tukey
>
>
> -----Oorspronkelijk bericht-----
> Van: r-help-bounces@r-project.org [mailto:r-help-bounces@r-project.org]
> Namens Dustin Fife
> Verzonden: dinsdag 29 mei 2012 14:56
> Aan: Rui Barradas
> CC: r-help
> Onderwerp: Re: [R] setting parameters equal in lm
>
> That did it. Thanks! One more follow-up questions. How do I set a
> parameter to a particular value? I tried I(.5*X2), but that didn't do what
> I expected.
>
> On Tue, May 29, 2012 at 6:39 AM, Rui Barradas <ruipbarradas@sapo.pt>
> wrote:
>
> > Hello,
> >
> > Your model is equivalent of
> >
> > y = b1(X1 + X3) + b2X2
> >
> > (plus error)
> >
> > So, use I() to add X1 and X3. You don't need to create an extra
> > variable
> > X13 <- X1 + X3. See the help page for it. The point on function formula.
> >
> > ?I
> >
> > linMod2 = lm(Y ~ -1 + I(X1  + X3) + X2, data=data.set)
> > summary(linMod2)
> > # The same.
> > linMod3 = lm(Y ~ 0 + I(X1  + X3) + X2, data=data.set)
> > summary(linMod3)
> >
> > With set.seed(1) your common slope is
> >
> > coef(linMod2)
> > I(X1 + X3)         X2
> >  0.4237869  3.3626984
> >
> > Also, I find it better to put 'library', 'require', etc as the first
> > lines of code.
> >
> > Hope this helps,
> >
> > Rui Barradas
> >
> > Em 29-05-2012 04:14, Dustin Fife escreveu:
> >
> >  Forgive me if this is a trivial question, but I couldn't find it an
> > answer
> >> in former forums. I'm trying to reproduce some SAS results where they
> >> set two parameters equal. For example:
> >>
> >> y = b1X1 + b2X2 + b1X3
> >>
> >> Notice that the variables X1 and X3 both have the same slope and the
> >> intercept has been removed. How do I get an estimate of this
> >> regression model? I know how to remove the intercept ("-1" somewhere
> >> after the tilde).
> >> But how about setting parameters equal? I have used the car package
> >> to set up linear hypotheses:
> >>
> >>
> >> X1 = rnorm(20, 10, 5); X2 = rnorm(20, 10, 5); X3 = rnorm(20, 10, 5) Y
> >> = .5*X1 + 3*X2 + .5*X3 + rnorm(20, 0, 15) data.set =
> >> data.frame(cbind(X1, X2, X3, Y)) linMod = lm(Y~X1 + X2 + X3,
> >> data=data.set)
> >> require(car)
> >> linearHypothesis(linMod, c("(Intercept)=0", "X1-X3=0"))
> >>
> >> (forgive the unconventional use of the equal sign....old habit).
> >> Unfortunately, the linearHypothesis is always compared to a full
> >> model (where the parameters are freely estimated). I want to have an
> >> ANOVA summary table for the reduced model. Any ideas? Thanks in
> >> advance for the help!
> >>
> >>
>
>
> --
> Dustin Fife
> PhD Student
> Quantitative Psychology
> University of Oklahoma
>
>         [[alternative HTML version deleted]]
>
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-- 
Dustin Fife
PhD Student
Quantitative Psychology
University of Oklahoma

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