Get better coverage

Protect Yourself





============================================================================================================== 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-h ... @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-h ... @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.