wow chuck. you really know how to dig up the archives. I don't know if it's
exactly relevant for what the OP is asking but i did use the
( or atleast a )Â paper by hotelling and it was titled "the selection of
variates for use in prediction with some comments on the general problem of
nusiance parameters. annals of mathematical statistics, 11, 271-283. joseph
lucke is not in that sequence of emails but I think he also helped me track
down relevant literature on it so credit goes to him also.
On Jul 7, 2010, Charles C. Berry <cbe...@tajo.ucsd.edu> wrote:
On Wed, 7 Jul 2010, chen jia wrote:
> Hi there,
>
> I run two regressions:
>
> y = a1 + b1 * x + e1
> y = a2 + b2 * z + e2
>
> I want to test against the null hypothesis: b1 = b2. How do I design the
test?
>
You are testing a non-nested hypothesis, which requires special handling.
The classical test is due to Hotelling, but see the references (and R code
snippets) in this posting:
http://markmail.org/message/egnowmdzpzjtahy7
(it is the merest coincidence that the above thread was initiated by Mark
Leeds and that the URL is 'markmail' :-) )
HTH,
Chuck
> I think I can add two equations together and divide both sides by 2:
> y = 0.5*(a1+a2) + 0.5*b1 * x + 0.5*b2 * z + e3, where e3 = 0.5*(e1 +
e2).
> or just y = a3 + 0.5*b1 * x + 0.5*b2 * z + e3
>
> If I run this new regression, I can test against the null b1 = b2 in
> this regression. Is it an equivalent test as the original one? If
> yes, how do I do that in R?
>
> Alternatively, I think I can just test against the null:
> correlation(y, x) = correlation(y, z), where correlation(. , .) is the
> correlation between two random variables. Is this equivalent too? If
> yes, how do I do it in R?
>
> Thanks.
>
> Best,
> Jia
>
> --
> Ohio State University - Finance
> 248 Fisher Hall
> 2100 Neil Ave.
> Columbus, Ohio 43210
> Telephone: 614-292-2830
> http://www.fisher.osu.edu/~chen_1002/
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
Charles C. Berry (858) 534-2098
Dept of Family/Preventive Medicine
E mailto:cbe...@tajo.ucsd.edu UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/ La Jolla, San Diego 92093-0901
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
