In article <[EMAIL PROTECTED]>, Vadim and Oxana Marmer <[EMAIL PROTECTED]> wrote:
> ... You can treat >regressors as non-stochastic if you have control over it. So, it seems to >me that the only case when you can treat regressors as fixed is when your >data is coming from some designed experiment. I do not know what is your >field of study, but if it's social science then you have a problem. In >social science most of the data is measurement of uncontrolled (by >researcher) processes and cannot be treated as fixed. What do you mean by "cannot"? What is it that goes wrong? Are you saying that the model will not make good predictions for new data from the same source? If so, I think you are wrong. Or are you saying that you won't be able to make conclusions about causal influences? That might well be, but for that, it's not really just a matter of "fixed" versus "stochastic". Radford Neal ---------------------------------------------------------------------------- Radford M. Neal [EMAIL PROTECTED] Dept. of Statistics and Dept. of Computer Science [EMAIL PROTECTED] University of Toronto http://www.cs.utoronto.ca/~radford ---------------------------------------------------------------------------- ================================================================= Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =================================================================
