"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/ . =================================================================
