Sounds something like Judgement analysis (JAN) which was used by folks like Bottenberg, Ward, and Schmid in the 60's and 70's. They studied how people made decisions by manipulating the characteristics of the situation and seeing (using a regression analysis) how the changes affected the decisions made. Thus, they did the regression separately for each person (each person examined many situations). This might be done in mixed models today. They also added cluster analysis to the mix by clustering the regression coefficients to group people whose decisions were affected the same way by changes in the attributes reported. You are likely to have small R squareds if you are right about the number of attributes but I doubt the tolerances would be a problem unless the attributes are highly correlated. Or unless you are doing as Bottenberg and others did and doing a regression on each person with only a few data points.
Paul R. Swank, Ph.D. Professor, Developmental Pediatrics Medical School UT Health Science Center at Houston -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]]On Behalf Of David Emery Sent: Wednesday, May 01, 2002 3:40 PM To: [EMAIL PROTECTED] Subject: Multiple regression and levels of interest 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/ . ================================================================= . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
