In article <[EMAIL PROTECTED]>, [EMAIL PROTECTED] says...
>
>We use multiple linear regression to perform our analyses. Because we
>work with binned data (discharge frequency of a neuron) which follow a
>non-normal (Poisson) distribution, we typically use the square root
>transform on the dependent variable (discharge rate of the neuron).
>(Actually, the transformation is sqrt(spike rate + 3/8) )
>
>I've been trying to show that some independent variables account for
>more of the variance explained in the dependent variable. However, some
>researchers in my field argue that the square root transform could
>artificially bias my results so that some independent variable account
>for more of the variance than they really should. I don't see how this
>could be from a theoretical level. Plus, I've run the multiple
>regression without the transform and seen only about a 5% difference
>(not much).
>
>Does anybody know if these criticisms have any theoretical merit? I
>can't see how this can be so. I thought that the square-root transform
>was a pretty sound way of reducing your chance of biasing the analysis
>if the data is non-normal (which most parametric tests require).
>
>Thanks.
>-Tony
>
>
>--
>///////////////////////////////////////////////////
>// G. Anthony Reina, MD //
>// The Neurosciences Institute //
>// 10640 John Jay Hopkins Drive //
>// San Diego, CA 92121 //
>// Phone: (858) 626-2132 //
>// FAX: (858) 626-2199 //
>////////////////////////////////////////////
You can try a straight Poisson regression. If the conclusions you obtained
from a Poisson regression are consistent with those from a square-root
transformation, you'd be OK. The main purpose of a square-root transform in
your case is to stabilize the variance of the error terms.
--
T.S. Lim
[EMAIL PROTECTED]
www.Recursive-Partitioning.com
______________________________________________________________________
Get paid to write a review! http://recursive-partitioning.epinions.com
===========================================================================
This list is open to everyone. Occasionally, less thoughtful
people send inappropriate messages. Please DO NOT COMPLAIN TO
THE POSTMASTER about these messages because the postmaster has no
way of controlling them, and excessive complaints will result in
termination of the list.
For information about this list, including information about the
problem of inappropriate messages and information about how to
unsubscribe, please see the web page at
http://jse.stat.ncsu.edu/
===========================================================================
