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> >> 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 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. [[alternative HTML version deleted]] ______________________________________________ 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.
