On 24 Dec 2003 15:06:00 -0800, [EMAIL PROTECTED] (Chih-Mao Hsieh) wrote: [ concerning Herman Rubin's note, on valuing linearity over 'normality' for factor analysis.] > If what is meant by linearity is basically left truncation, then I have understood > it... >
No. I see in my previous response, that you raised an issue about zeros. I think that Herman was saying -- All these variables are expected to be, by their measurement as well as their nature, generally "linear" in predicting each other. That is often difficult to achieve with "counts" when there is a conflict between (a) the Poisson-sort of variability, where one might expect square-roots of counts to have a better scaling property; and (b) the unit-per-unit increase in quantities that can be inherent. What comes to my mind is the similar difficulty that I see in constructing certain sorts of models of utility, in economics: In terms of "importance", and magnitudes of change over time, it is desirable to take the logarithm of dollar amounts. Doubling the dollars does not double the satisfaction. However, what you can *purchase* with 'dollars' is apt to increase in that dumb linear fashion, or be even faster. By the way, back to the original post: IF the result of a test for 'non-normality' is 'significant' only by virtue of testing it with the power of many thousands of observations, that would be even further reason to discount the concern about normality. [ snip, rest] -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html "Taxes are the price we pay for civilization." . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
