Dear Steven, > -----Original Message----- > From: Steven Yen [mailto:sye...@gmail.com] > Sent: June 29, 2016 9:48 AM > To: Fox, John <j...@mcmaster.ca> > Cc: R-help <r-help@r-project.org>; Sandy Weisberg (sa...@umn.edu) > <sa...@umn.edu> > Subject: Re: [R] t-test for regression estimate > > Also, > Is there a way to get the second command (hypothesis defined with externally > scalars) below to work? Thanks. > > linearHypothesis(U,"0.5*eq1_DQ+0.3*eq2_DQ",verbose=T) > w1<-0.5; w2<-0.3 > linearHypothesis(U,"w1*eq1_DQ+w2*eq2_DQ",verbose=T) # does not work
You can specify the hypothesis matrix (a vector in the 1-df case). E.g., ----------------- snip --------------------- > library(car) > mod <- lm(prestige ~ income + education, data=Duncan) > one <- 1 > minus.one <- -1 > linearHypothesis(mod, c(0, one, minus.one)) # 0 * the intercept Linear hypothesis test Hypothesis: income - education = 0 Model 1: restricted model Model 2: prestige ~ income + education Res.Df RSS Df Sum of Sq F Pr(>F) 1 43 7518.9 2 42 7506.7 1 12.195 0.0682 0.7952 ----------------- snip --------------------- John > > > On 6/29/2016 12:38 PM, Steven Yen wrote: > > > Thanks John. Yes, by using verbose=T, I get the value of the hypothesis. > But tell me again, how would I get the variance (standard error)? > > > On 6/29/2016 11:56 AM, Fox, John wrote: > > > Dear Steven, > > OK -- that makes sense, and there was also a previous request > for linearHypothesis() to return the value of the hypothesis and its > covariance > matrix. In your case, where there's only 1 numerator df, that would be the > value and estimated sampling variance of the hypothesis. > > I've now implemented that, using (at least provisionally) > attributes in the development version of the car package on R-Forge, which you > should be able to install via install.packages("car", repos="http://R-Forge.R- > project.org" <http://R-Forge.R-project.org> ). Then see ?linearHypothesis for > more information. > > Best, > John > > > -----Original Message----- > From: Steven Yen [mailto:sye...@gmail.com] > Sent: June 28, 2016 3:44 PM > To: Fox, John <j...@mcmaster.ca> > <mailto:j...@mcmaster.ca> > Cc: R-help <r-help@r-project.org> <mailto:r-help@r- > project.org> > Subject: Re: [R] t-test for regression estimate > > Thanks John. Reason is I am doing linear > transformations of many coefficients > (e.g., bi / scalar). Of course I can uncover the > t-statistic > from the F statistic and > then the standard error. Simply scaling the estimated > coefficients I can also > transform the standard errors. I have since found > deltaMethod from library > "car" useful. Its just that, if linearHypothesis had > provide the standard errors > and t-statistics then the operation would have been > easier, with a one-line > command for each coefficient. Thank you again. > > > On 6/28/2016 6:28 PM, Fox, John wrote: > > > Dear Steven, > > The reason that linearHypothesis() computes a > Wald F or chisquare > test rather than a t or z test is that the (numerator) > df > for the linear hypothesis > need not be 1. > > In your case (as has been pointed out) you can > get the coefficient > standard error directly from the model summary. > > More generally, with some work, you could > solve for the the SE for a 1 > df linear hypothesis in terms of the value of the linear > function of coefficients > and the F or chisquare. That said, I'm not sure why you > want to do this. > > I hope this helps, > John > > ----------------------------- > John Fox, Professor > McMaster University > Hamilton, Ontario > Canada L8S 4M4 > Web: socserv.mcmaster.ca/jfox > > > > -----Original Message----- > From: R-help [mailto:r-help- > boun...@r-project.org] On Behalf > Of Steven Yen > Sent: June 28, 2016 9:27 AM > To: R-help <r-help@r-project.org> > <mailto:r-help@r-project.org> <mailto:r-help@r- > project.org> <mailto:r-help@r-project.org> > Subject: [R] t-test for regression > estimate > > test option for linearHypothesis in > library(car) include "Chisq" > and "F". I prefer > a simple t-test so that I can retrieve > the standard error. > Any options other than > linearHypothesis to test the linear > hypothesis (with 1 > restriction/degree of freedom)? > > > summary(ols1) > > Coefficients: > Estimate Std. Error t value > Pr(>|t|) > (Intercept) -0.20013 0.09199 -2.176 > 0.0298 * > age 0.04054 0.01721 2.355 > 0.0187 * > suburb 0.01911 0.05838 0.327 > 0.7435 > smcity -0.29969 0.19175 -1.563 > 0.1184 > --- > Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 > ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > > > linearHypothesis(ols1,"suburb") > Linear hypothesis test > > Hypothesis: > suburb = 0 > > Model 1: restricted model > Model 2: polideo ~ age + suburb + > smcity > > Res.Df RSS Df Sum of Sq F > Pr(>F) > 1 888 650.10 > 2 887 650.02 1 0.078534 0.1072 > 0.7435 > > > [[alternative HTML version > deleted]] > > > ______________________________________________ > R-help@r-project.org <mailto:R- > h...@r-project.org> <mailto:R-help@r-project.org> <mailto:R-help@r- > project.org> mailing > list -- To UNSUBSCRIBE and more, see > > 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 -- To UNSUBSCRIBE and more, see 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.