On Fri, 18 Jan 2008, Darren Weber wrote: > How do we get 2-tailed p-values for the rlm summary? > > I'm using the following: > >> fit <- rlm(oatRT ~ oatoacData$erp, psi=psi.bisquare, maxit=100, > na.action='na.omit') >> fitsum <- summary(fit, cor=F) >> print(fitsum) > > Call: rlm(formula = oatRT ~ oatoacData$erp, psi = psi.bisquare, maxit = 100, > > na.action = "na.omit") > Residuals: > Min 1Q Median 3Q Max > -120.616 -50.637 -5.895 60.356 199.066 > > Coefficients: > Value Std. Error t value > (Intercept) 574.5204 25.8582 22.2181 > oatoacData$erp 11.5963 5.3525 2.1665 > > Residual standard error: 83.29 on 36 degrees of freedom > (2 observations deleted due to missingness) >> i <- length(fitsum$coefficients) - dim(fitsum$coefficients)[1] + 1 >> j <- length(fitsum$coefficients) >> tvalues <- fitsum$coefficients[i:j] >> pvalues <- pt(tvalues, df=fitsum$df[2]) >> print(rbind(tvalues, pvalues)) > [,1] [,2] > tvalues 22.21815 2.1664977 > pvalues 1.00000 0.9815145 > > > If I use the lower.tail=FALSE argument to pt, then I seem to get only the > p-values for anything > my t value. Do have to call pt twice, once with > lower.tail=TRUE and once with lower.tail=FALSE to get 2-tailed p-values?
The t distribution is symmetric, so you just double the upper tail value. (See the code of summary.lm for how it does this.) BUT, what justifies the assumption of a t distribution here? Even for lm, the calculations rely on a normal distribution of errors, and robust methods are used precisely to avoid that. rlm() is support software for a book, and this issue and alternatives (e.g. bootstrapping) are discussed there. > > Thanks in advance, Darren > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. > -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ 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.
