David, this sounds suspiciously like "conjoint analysis," which was documented pretty well by Paul E. Green, Harvard Business Review, July-August 1975, pp. 107-117. And a number of other papers since and before.
If you decide that the response of interest is "viewer level of interest" in a presentation, and that there are specific things you can change about the presentations, in such a way that you can control if a feature/characteristic is on or off, or how much of it is present, then you can perform a conjoint analysis. the math is almost exactly equal to that of a classical designed experiment. the measurement of 'level of interest' requires some assumptions, of which Tukey & Green explained very completely in the 1960's. Some ref's on request. I've done it a number of times, with fascinating success each time. there are always an infinite number of possible attribute changes that could be included in such an experiment. Your prior knowledge/insight about videos and what is interesting about them can narrow that down to a dozen or more, that are _likely_ to do something interesting. Your interest in keeping the trials within rational, executable bounds, will force you to select 4 to 10 factors (changeable attributes). the big problem in my view is, how are you going to expose the respondents to the different videos? The order of exposure may cause serious evaluation & interpretation issues, which you will need to address also. BTW, 'multiple regression' is a generalized form of designed experiment, only without the careful planning and without the ease of interpretation. OK, DoE is a subset of multiple regression. OK, the mathematical analysis is the same, but the DoE is more informative, when it is done properly. Now shoot me. Jay David Emery wrote: > I'm a student trying to see how mulitple regression might be used to > predict levels of interest in interactive video presentations based on > pre-picked attributes of the content in the video. My question is > whether anyone has seen anything done like this before, academic or > proprietary?? Has anyone seen this done using a different method of > analysis? > > Since there are potentially millions of attributes that could affect > interest (or some large unknown number), and only 4 are really > examined, the expected levels of significance are very small for each > attribute. Is this Ok as long as the Variance Influence Factors and > other error levels are within tolerance? > > Thanks, > David > . > . > ================================================================= > Instructions for joining and leaving this list, remarks about the > problem of INAPPROPRIATE MESSAGES, and archives are available at: > . http://jse.stat.ncsu.edu/ . > ================================================================= -- Jay Warner Principal Scientist Warner Consulting, Inc. 4444 North Green Bay Road Racine, WI 53404-1216 USA Ph: (262) 634-9100 FAX: (262) 681-1133 email: [EMAIL PROTECTED] web: http://www.a2q.com The A2Q Method (tm) -- What do you want to improve today? . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
