[R] Calculating p-value for 1-tailed test in a linear model

Andrew Campomizzi acampomizzi at tamu.edu
Mon Aug 22 15:44:59 CEST 2011


David,
It's fair to question my intentions.  I'm running power analyses using
simulations (based on Bolker's Ecological Models and Data in R) and need to
provide decision-makers with options.  So, I'm attempting to make it clear
that if the research hypothesis (e.g., response variable declines with an
increase in predictor variable) can be clearly answered with a 1-tailed
test, then one might need a sample size of n to get a particular power,
given variance and alpha.
I think Mark's response answers my question.
Thanks,
Andy

-----Original Message-----
From: David Winsemius [mailto:dwinsemius at comcast.net] 
Sent: Saturday, August 20, 2011 6:02 PM
To: Andrew Campomizzi
Cc: r-help at r-project.org
Subject: Re: [R] Calculating p-value for 1-tailed test in a linear model


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



More information about the R-help mailing list