LISTSERV at the University of Georgia
Menubar Imagemap
Home Browse Manage Request Manuals Register
Previous messageNext messagePrevious in topicNext in topicPrevious by same authorNext by same authorPrevious page (October 2006)Back to main SPSSX-L pageJoin or leave SPSSX-L (or change settings)ReplyPost a new messageSearchProportional fontNon-proportional font
Date:   Fri, 27 Oct 2006 10:53:39 -0700
Reply-To:   peter link <plink@vapop.ucsd.edu>
Sender:   "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:   peter link <plink@vapop.ucsd.edu>
Subject:   Re: small sample-repeated predictors-more
In-Reply-To:   <c82.5f53193.3272b027@aol.com>
Content-Type:   text/plain; charset="US-ASCII"

Roland -

For your hypothetical example of many people observed many times, I would recommend MIXED procedure (or some other software for Multilevel Modelling - HLM, MLwin, MIXOR, SAS Proc Mixed, to name a few). To reiterate, linear regression is not advised in this situation due to assumptions not being met (non-independent observations, [E(ei * ej) does not equal 0].) If interested in this approach see Singer & Willett, Applied Longitudinal Data Analysis, Oxford University Press, 2003.

Peter -----Original Message----- From: Rcarlstedt@aol.com [mailto:Rcarlstedt@aol.com] Sent: Thursday, October 26, 2006 5:43 PM To: Peter Link; SPSSX-L@LISTSERV.UGA.EDU Subject: Re: small sample-repeated predictors-more

In a message dated 10/26/2006 8:18:01 PM Eastern Standard Time, plink@vapop.ucsd.edu 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 RCarlstedt@americanboardofsportpsychology.org 917-680-3994


Back to: Top of message | Previous page | Main SPSSX-L page