Posted by
Rcarlstedt on
Oct 27, 2006; 1:43am
URL: http://spssx-discussion.165.s1.nabble.com/Re-small-sample-repeated-predictors-more-tp1071739p1071740.html
In a message dated 10/26/2006 8:18:01 PM Eastern Standard Time,
[hidden email] writes:
I wouldn't suggest doing linear regression on a single individual using just
pre- and post. If you would do it this way, why not use all of the data
points, not just pre- and post-? That would make more sense to me.
The reason for this was that in the pre-condition HRV was only monitored (5
predictor HRV measures), in the second post condition the player engaged in an
intervention that manipulated HRV while being monitored. In both cases I
wanted to find correlations between predictors and outcome measures and variance
explained through multiple regression and then compare differences (i.e.,
was more of the variance explained in outcome on the basis of HRV post compared
to pre-no intervention).
Esentially, you are saying even if one has hundreds of measures obtained
through hundreds of measurement occasions that are hypothesized to predict and
correspond to specific outcome measures (each HRV data point corresponds to an
outcome [HRV-low frequency and say, batting result]) one should/cannot
validly use multiple regression to determine variance explained?
Thanks again!
Roland
__________________________________________
Roland A. Carlstedt, Ph.D.
Licensed Clinical Psychologist/Licensed Applied Psychologist
Clinical and Research Director: Integrative Psychological Services of NYC
Chair and Head Mentor: American Board of Sport Psychology
Research Fellow in Applied Neuroscience: Brain Resource Company
_www.americanboardofsportpsychology.org_
(
http://www.americanboardofsportpsychology.org/)
[hidden email]
917-680-3994