OK. Thanks again. I will read the references more.
Best, Jia On Thu, Jul 8, 2010 at 10:51 AM, <markle...@verizon.net> wrote: > hi: no. it's not the same. if you read the paper that I referenced last > night, that explains how to do the following test : > > Ho: R2 = R1 > > H1: R2 != R1 > > that's a different test from what you did but i think it's what you want. > > > > > On Jul 8, 2010, chen jia <chen_1...@fisher.osu.edu> wrote: > > Thanks, Chuck. I am reading the references, which are helpful. > > Just to understand what I have done wrong here, > > I proposed an alternative testing strategy: > I run regressions y = a3 + b1 * x + b2 * z + e3 and test alternative > hypothesis b1 != b2 against the null hypothesis b1 = b2 in this > equation. > > Is it this the same test as > > y = a1 + b1*x + e1 > y = a2 + b2*x + e2 > test alternative hypothesis b1 != b2 against null hypothesis b1 = b2. > > Best, > Jia > > On Wed, Jul 7, 2010 at 11:12 PM, 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 >> >> >> > > > > -- > 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. > -- 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.
