Rich Ulrich wrote (in part) <<< Finally, some people like arbitrary transformations, including adding arbitrary constants before taking the log or power: What I am thinking of are the ones with the single virtue of giving residuals that are apparently normal, for the data on hand -- That is done in order to improve (or justify) using the F-test. The proper p-level is not achieved if you do not meet the assumption about residuals, so this DOES THAT. I can admit that I did that a time or two, a long time ago, and I might someday do it again. However, the F-test will be more simply wrong, if, say, the linearity is fouled up by the transformation, making the coefficients wrong and mis-measuring the error. I don't know if I avoid 'arbitrary transformations' because of that, or because they are inelegant and hard to justify to anyone else. >>>
I think an additonal point for (or against) such arbitrary transformations is whether the original scale has any intrnisic meaning, or whether the transformation does. If the DV is some scale score, where the scale is largely unknown and arbitrary, then it is less 'inelegant' and easier to justify than a similar transformation where the original scale is not arbitrary, or is well known. e.g. If the DV is (say) weight, then there may be substantive justification for taking logs, or for using the original variable; I would be more hesitant to use a BoxCox transform, largely because it's harder to interpret. OTOH, if the DV is some score on some test that no one's ever heard of, then the original scale is totally arbitrary, so transforming it doesn't make it MORE arbitrary. (Of course, all this assumes that the transformation solves more problems than it causes.....) Peter Peter L. Flom, PhD Assistant Director, Statistics and Data Analysis Core Center for Drug Use and HIV Research National Development and Research Institutes 71 W. 23rd St www.peterflom.com New York, NY 10010 (212) 845-4485 (voice) (917) 438-0894 (fax) . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
