Dear Vito, Since Manuel says that he wants to "obtain a test" and not "obtain two tests," I assume that he's interested in the F-test for the hypothesis that both coefficients are simultaneously equal to the specified values rather than in the t-tests for the individual hypotheses.
Regards, John -------------------------------- John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox -------------------------------- > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Vito Ricci > Sent: Friday, February 11, 2005 3:30 AM > To: [email protected] > Cc: [EMAIL PROTECTED] > Subject: [R] Re: testing slopes different than a given value > > Hi, > > We know that a regression coefficent fitted by sample data > (under usual linear model hypothesis) b_hat has mean=b and > se=se(b_hat); (b_hat-b)/s(b_hat) is distributed as Student's > t distribution with df=n-2. > So you can test h0:b=b0 hA:b<>b0 using t test (for large > sample normal distribution is the same of a t > distribution): > > x1<-rnorm(100) > x2<-rnorm(100) > e<-rnorm(100) > y<-3+0.6*x1+0.3*x2 +e > fm<-lm(y~x1+x2) > > > summary(fm) > > Call: > lm(formula = y ~ x1 + x2) > > Residuals: > Min 1Q Median 3Q Max > -2.17610 -0.65146 -0.09532 0.54848 2.41966 > > Coefficients: > Estimate Std. Error t value Pr(>|t|) > (Intercept) 3.04924 0.09661 31.562 < 2e-16 *** > x1 0.55124 0.09930 5.551 2.47e-07 *** > x2 0.23477 0.10534 2.229 0.0281 * > --- > Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' > 0.1 ` ' 1 > > Residual standard error: 0.9492 on 97 degrees of freedom > Multiple R-Squared: 0.2687, Adjusted R-squared: > 0.2536 > F-statistic: 17.82 on 2 and 97 DF, p-value: 2.561e-07 > > b<-coef(fm) > > b > (Intercept) x1 x2 > 3.0492374 0.5512398 0.2347682 > you get b_hat standard errors from summary(fm): > > se<-c(0.09661,0.09930,0.10534) > > se > [1] 0.09661 0.09930 0.10534 > > ttest<-(b[2]-0.6)/se[2] > > > ttest > x1 > -0.4910391 > > 1-pt(ttest,df=97) ##p-value, as df is high we can > use normal distribution > x1 > 0.687746 > > we accept h0 :b1=0.6; > > Hoping I helped you. > Best regards, > Vito > > You wrote: > In a multiple linear regression with two independent > variables is there any function in R to test for the > coefficients being different than some given values? > Example: > x1<-rnorm(100) > x2<-rnorm(100) > y<-3+0.6*x1+0.3*x2 > fm<-lm(y~x1+x2) > Obtain a test for the coefficients for x1 being different > than 0.6 and for x2 different than 0.3 Thanks Manuel > > > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
