[R] Power calculation with measurement error

Greg Snow Greg.Snow at intermountainmail.org
Tue Jun 26 17:18:02 CEST 2007

```I don't know of a current package that does this (others may), but if
you know what you expect your data to look like you can simulate it and
calculate power that way.

Basically, write a function that will simulate data with the level of
measurement error that you expect in the real data (or have the amount
of measurement error passed in as a parameter so you can examine the
effect of diffenent values).  Then have the function compute the t test
(or other test that you plan to do) and return the p-value from the
test.

Then you can simulate the process with a command like:

> out1 <- replicate( 1000, myfunction(n=25, err=.1, diff=.5) )

And compute the power with:

> mean( out1 < 0.05 ) # or whatever alpha value you want.

Hope this helps,

--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at intermountainmail.org
(801) 408-8111

> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Mike Lawrence
> Sent: Tuesday, June 26, 2007 5:13 AM
> To: Rhelp
> Subject: [R] Power calculation with measurement error
>
> Hi all,
>
> Hopefully this will be quick, I'm looking for pointers to
> packages/ functions that would allow me to calculate the
> power of a t.test when the DV has measurement error. That is,
> I understand that, ceteris paribus, experiments using measure
> with more error (lower
> reliability) will have lower power.
>
> Mike
>
> --
> Mike Lawrence
> Graduate Student, Department of Psychology, Dalhousie University
>
> Website: http://memetic.ca
>
> Public calendar: http://icalx.com/public/informavore/Public
>
> "The road to wisdom? Well, it's plain and simple to express:
> Err and err and err again, but less and less and less."
> 	- Piet Hein
>
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