Let me ask you guys this. If you calculated the power for
the Chi-Squared test using both a small and then a large numbers and did
the same for the KS test what would you find?
In article <8c4vhs$e75$[EMAIL PROTECTED]>,
[EMAIL PROTECTED] wrote:
> Herman Rubin ([EMAIL PROTECTED]) wrote:
> : How should one decide which type of test to use EXCEPT by
> : looking at its power? Statistics is not a collection of
>
> Minor details like validity come to mind. But you're exactly right,
> Herman, among tests that are valid, power is certainly an important,
if
> not the most important, criterion. But tests are sometimes chosen that
> have a reputation for high power against corner-case alternatives over
> more general tests, when these alternatives are not likely for the
> context in question. Computability (both of the test statistic and its
> critical values), though less often an issue, is also a relevant
> criterion. Finally, interpretability and understandability are
> relevant. A test or diagnostic (e.g. Q-Q or P-P plots) that gives
> richer information than just a p-value may be much more valuable than
a
> blind test. I've seen cases where a test was originally chosen over
> another because it was theoretically superior, but the superiority was
> in the sixth decimal place and the method was completely
unintelligible
> to the intended audience (this was an application journal). Of course,
> something to consider is multiple approaches: some more interpretable
> and others perhaps chosen for theoretical superiority. It might be
> worth pointing out that if you haven't done a histogram or Q-Q plot,
> you have no business performing a test.
>
> So yes, there are other criteria than power, but this is the first
> and perhaps most important criterion to consider.
>
> --
> Clark K. Gaylord
> Senior Research Engineer
> Communications Network Services
> Virginia Tech, Blacksburg, Virginia 24061-0506
> Voice: 540/231-2347 Fax: 540/231-3928 E-mail: [EMAIL PROTECTED]
>
--
Madewell
Interests: Engineering Management, Reliability Engineering,
Failure Analysis, Statistical Methods.
Sent via Deja.com http://www.deja.com/
Before you buy.
===========================================================================
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/
===========================================================================
