Thom Baguley <[EMAIL PROTECTED]> wrote:
>> You can get important significant effects, unimportant significant
>> effects, important non-significant effects and unimportant
>> non-significant effects.
Radford Neal wrote:
>I'll go for three out of four of these. But "important non-significant
>effects"?
>
>That would be like saying "I think the benefits of this drug are large
>enough to be important, even though I'm not convinced that it has any
>benefit at all".
Richard M. Barton <[EMAIL PROTECTED]> wrote:
> ***I disagree. It could indicate lack of power. If your alpha
> level had been higher, or if you had more subjects, you might have
> found statistically significant results.
Yes, if you did an experiment using more subjects you MIGHT obtain
convincing evidence that the drug really does have a benefit. Or you
might not. This is no different from what you could have said even
before you did the first experiment. This POSSIBILITY doesn't justify
saying that you found an "important but non-significant" effect. If
you're trying to say that the experiment produced some evidence of a
benefit, and that this evidence is enough to persuade you to recommend
use of the drug, even though it's still possible that there is no real
benefit, then I think that p-values are too crude a tool for what you
want to do. You need to use Bayesian decision theory.
Radford Neal
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Radford M. Neal [EMAIL PROTECTED]
Dept. of Statistics and Dept. of Computer Science [EMAIL PROTECTED]
University of Toronto http://www.cs.utoronto.ca/~radford
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