Campomizzi, Andrew J <acampomizzi <at> neo.tamu.edu> writes: > On 20/08/11 10:20, Andrew Campomizzi wrote: > > Hello, > > > > I'm having trouble figuring out how to calculate a p-value for a 1-tailed > > test of beta_1 in a linear model fit using command lm. My model has only 1 > > continuous, predictor variable. I want to test the null hypothesis beta_1 > > is>= 0. I can calculate the p-value for a 2-tailed test using the code > > "2*pt(-abs(t-value), df=degrees.freedom)", where t-value and degrees.freedom > > are values provided in the summary of the lm. The resulting p-value is the > > same as provided by the summary of the lm for beta_1. I'm unsure how to > > change my calculation of the p-value for a 1-tailed test. > >
Isn't it just pt(tvalue,df=degrees.freedom,lower.tail=FALSE) if the value is positive (and expected to be positive) or pt(tvalue,df=degrees.freedom) if the value is negative (and expected to be negative)? In fact, if the value is in the expected direction, I think you can just leave out the multiplication by 2 and get the right answer ... ______________________________________________ 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.
