Dave -- If you "can't control it, then measure it" and include it in your model. That's the VALUE of using RERESSION/LINEAR MODELS for your analyses.
-- Joe ********************************** Joe H. Ward, Jr. 167 East Arrowhead Dr. San Antonio, TX 78228-2402 Phone: 210-433-6575 Fax: 210-433-2828 Email: [EMAIL PROTECTED] http://www.northside.isd.tenet.edu/healthww/biostatistics/wardindex ============================== Health Careers High School 4646 Hamilton Wolfe Road San Antonio, TX 78229 ********************************** ----- Original Message ----- From: "Jos Jansen" <[EMAIL PROTECTED]> To: <[EMAIL PROTECTED]> Sent: Tuesday, August 19, 2003 8:58 AM Subject: Re: Exp. design: Controlling for an unknown variable > "Dave Jeffries" <[EMAIL PROTECTED]> schreef in bericht > news:[EMAIL PROTECTED] > > Hi there everyone, > > > > I'm trying to set up the analysis for some water research, and I'm > > hoping to elicit some advice. So far the bulk is a 2 or 3 factorial > > design (to be decided later) with no interaction expected. However, > > there is one other variable that I can't control - as I said, it's > > water research, and each sample will be collected discretely, albeit > > from the same source, but on different days. There is NO WAY to > take > > multiple samples at the same time and store some for later analysis, > > as each treatment/test will take over 48 hours to run, and the > sample > > would change anyway. While I don't expect any significant changes > in > > the samples collected before each test, I need to confirm it. > > > > So far, the best method I could come up with is to have a control > > treatment, one that is run every 3 or 4 treatments throughout the > > entire experiment, and then do a run-test on the response from it. > > Then, if the responses are close enough to be accepted as statis. > > insignificant, just assume that there was no change through the > other > > tests as well. > > > > However, what I'd like to do is find a more robust method that works > > the last bit into the factorial design, perhaps through replication, > > but without letting the number of tests required get to large. If > > there's anyone out there who might be able to come up with some idea > > of how to check this uncontrollable variable, I'd greatly appreciate > > your thoughts on the matter. > > > > The traditional way of handling uncontrollable variation is to > randomize treatments over experimental units, i.c. days. Variation > between days will thus be contained in your estimate of residual > variance, which subsequently will be used for estimating the precision > of treatment effects. > > . > . > ================================================================= > Instructions for joining and leaving this list, remarks about the > problem of INAPPROPRIATE MESSAGES, and archives are available at: > . http://jse.stat.ncsu.edu/ . > ================================================================= . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
