On Tue, 13 Mar 2001, Will Hopkins wrote in part:
> Example: you observe an effect of +5.3 units, one-tailed p = 0.04.
> Therefore there is a probability of 0.04 that the true value is less
> than zero.
Sorry, that's incorrect. The probability is 0.04 that you would find an
effect as large as +5.3 units (or more), if (a) the true value is zero
and (b) the sampling distribution of the test statistic is what you think
it is. (The probability of finding an effect this large, in this
direction, is less than 0.04 if the true value is less than zero (and
your sampling distribution is correct).)
< snip >
> But why test at all? Just show the 95% confidence limits for your
> effects, and interpret them: "The effect could be as big as <upper
> confidence limit>, which would mean.... Or it could be <lower
> confidence limit>, which would represent... Therefore... " Doing it
> in this way automatically addresses the question of the power of your
> study, which reviewers are starting to ask about. If your study turns
> out to be underpowered, you can really impress the reviewers by
> estimating the sample size you would (probably) need to get a
> clear-cut effect. I can explain, if anyone is listening...
You had in mind, I trust, the _two-sided_ 95% confidence interval!
-- Don.
----------------------------------------------------------------------
Donald F. Burrill [EMAIL PROTECTED]
348 Hyde Hall, Plymouth State College, [EMAIL PROTECTED]
MSC #29, Plymouth, NH 03264 (603) 535-2597
184 Nashua Road, Bedford, NH 03110 (603) 471-7128
=================================================================
Instructions for joining and leaving this list and remarks about
the problem of INAPPROPRIATE MESSAGES are available at
http://jse.stat.ncsu.edu/
=================================================================
