Thank you John and Peter. Peter, yes I'm guilty of tacking onto a random mail. I thought you couldn't tell since I got ride of the text from the last mail. Apologize.
H. >>> "John Fox" <[EMAIL PROTECTED]> 3/28/2007 5:37 PM >>> Dear Horace, The Bonferonni p-value is obtained from the "unadjusted" p-value by multiplying the latter by the number of observations, and provides a conservative (although usually quite accurate) outlier test. When the adjusted p-value exceeds 1 you can take that as an indication that there are no unusually large studentized residuals (and indeed that the largest studentized residual is smaller than one would expect under the standard linear-model assumptions). I hope this helps, 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 Horace Tso > Sent: Wednesday, March 28, 2007 6:36 PM > To: 'R R-help' > Subject: [R] Bonferroni p-value greater than 1 > > Hi folks, > > I use the outlier.test in package car to test a lm model and > the bonferroni p value returned is shown as NA. When the > object is typed it indicates the p value is greater than 1. > I'm not sure how to interpret it. > > Thanks in advance. > > Horace W. Tso > > > > outlier.test(mod)$test > max|rstudent| df unadjusted p Bonferroni p > 2.04106376 18.00000000 0.05618628 NA > > > outlier.test(mod) > > max|rstudent| = 2.041064, degrees of freedom = 18, > unadjusted p = 0.05618628, Bonferroni p > 1 > > Observation: 1 > > The lm model looks fine to me, > > > summary(mod) > > Call: > lm(formula = x ~ ind, na.action = na.fail) > > Residuals: > Min 1Q Median 3Q Max > -1.2082 -0.5200 0.1309 0.5725 0.9593 > > Coefficients: > Estimate Std. Error t value Pr(>|t|) > (Intercept) 59.84586 0.31900 187.6 < 2e-16 *** > ind -0.16768 0.02541 -6.6 2.57e-06 *** > --- > Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > > Residual standard error: 0.705 on 19 degrees of freedom > Multiple R-Squared: 0.6963, Adjusted R-squared: 0.6803 > F-statistic: 43.56 on 1 and 19 DF, p-value: 2.57 > > ______________________________________________ > R-help@stat.math.ethz.ch 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. > ______________________________________________ R-help@stat.math.ethz.ch 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.
