While randomization ideally eliminates the need for pre-measurement, in
practice group sizes of 5 are insufficient to insure a reasonable
probability the randomization was successful. See Hsu (1989, Journal of
Consulting and Clinical Psychology).
--
Robert McGrath, Ph.D.
Professor
School of Psychology T110A, Fairleigh Dickinson University, Teaneck NJ 07666
voice: 201-692-2445 fax: 201-692-2304 [EMAIL PROTECTED]
On Wed, 8 Dec 1999, Magill, Brett wrote:
> Mike,
>
> With randomization pre, it is not necessary to take a pre-intervention
> measurement. Test the difference in confidence following the training. If
> it is significant, there is a difference. Decide what direction it is in
> and attribute the difference to the training. You can make this attribution
> because of random assignment even without pre-measure.
>
> -----Original Message-----
> From: Mike Wogan [mailto:[EMAIL PROTECTED]]
> Sent: Wednesday, December 08, 1999 2:16 PM
> To: Luv 2 muah 143
> Cc: [EMAIL PROTECTED]
> Subject: Re: could someone help me with this intro to stat. problem
>
>
> On 8 Dec 1999, Luv 2 muah 143 wrote:
>
> > 5 of 10 volunteers are randomly selected to receive self-defense training.
> The
> > other 5 receive no training. At the end of the training period, all
> subjects
> > complete a self-confidence questionnaire.
> >
> > a.) Is there a difference in self-confidence between the 2 groups
> (p<.01)?
> >
> >
> > b.) What are the effects of self-defense traing on self-confidence (I'm
> > assuming a two-tailed test?). Explain analysis
> >
> > Please help, I can't figure it out...my mind has gone blank!!!!
>
> Without a pre-test measure of self-confidence, taken prior to the
> training, even if there is a significant difference post-training, it's
> not possible to tell whether the difference is the result of the training
> or was there to begin with.
>
> If there is a pre-post measurement of self-confidence, then you need a
> mixed model Anova, with Training vs. No Training as the between groups
> factor and Pre-Post as the within groups factor.
>
> Mike
>
>
