let's say that one designs a simple experiment about the effectiveness of a
weight change program ...
you set your sights on a power of .7 ... (beta therefore being .3) ...
select a two tailed alpha of .05 ... because the situation is such that
this program could actually make you gain weight .... though you hope that
it will help you lose weight
now, let's assume that you want to detect an effect of 3 pounds ... either
gain or loss ... and you therefore go about estimating the n needed to
achieve this goal of being able to reject the null with a p of .7 ... if in
fact the null is not true ... and the gap between the null and the center
of the treatment effect distribution being 3 ...
now, what if you execute your study rigorously with the n you estimated you
would need ... and then reject the null with a p = .02 (for illustration
purposes only) ... at the moment, don't worry if it is a gain or loss ...
just that you reject the null
here is my question (you were wondering when i would get to it, right?)
WHAT CAN WE SAY, BASED ON THIS REJECTION OF THE NULL, about the treatment
effect being 3 lbs OR more ... ?
what confidence do we have that the treatment effect is AT LEAST 3 lbs?
===========================================================================
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/
===========================================================================
