On Aug 19, 2011, at 6:20 PM, 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.
You need to clearly state your hypothesis. Then using the output from
the regression function should be straightforward.
(Yes. this is a intentionally vague answer designed to elicit further
information about your understanding of the statistical issues and how
they relate to your domain knowledge. Many time peole already have the
data and because they didn't get the answer they wanted, they search
for other ways to "game the system" by ad-hoc changes in the
statistical "rules of the road".)
--
David Winsemius, MD
West Hartford, CT
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