I suggest looking at the books Tukey co-authored, for help with basic ideas of scoring and scaling. Others might have additional suggestions.
On 18 Jun 2003 15:14:24 -0700, [EMAIL PROTECTED] (Dianne Worth) wrote: > It is my understanding that if the data distribution is positively > skewed , one can take a log of the data. One CAN, and it might help. And it *might* be a totally ignorant, wrong-headed thing to do. It is not surely not automatic. One might also take the square root, or the reciprocal, or form groups out of scores. Or, one might suffer no harm from leaving them alone; or, one might suffer harm but *still* be best-advised to leave them alone. > If it's negatively skewed, > one should 'flip' it by adding 1 to the largest value, and a series of > steps that are probably best explained as follows: It is certainly a good idea to *consider* the meaning of reversing the scores, especially when you have scores (as you seem to) that are integer scale-scores. On the other hand, as *automatic* advice, that is totally stupid, starting with "adding 1". And if they are scale-scores, the square root is more likely to suit, than the log. For negative integers, the obvious change is to add enough so the bottom is zero, or to reverse them. - Where do the numbers come from? - that probably suggests which makes more sense for making them positive. Where do the numbers come from? Are they so abstract that there is never any harm done, to their meaning, by taking any arbitrary transformation? If you don't know anything more than "order", it might be wise to rank-transform them. (I usually consider ranking a pretty weak step to take -- It is an admission that the data-collection was poor enough, we can not extract any information beyond the 'ordering'.) -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html "Taxes are the price we pay for civilization." Justice Holmes. . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
