On Wed, 17 Oct 2001 15:50:35 +0200, Tobias Richter <[EMAIL PROTECTED]> wrote:
> > > We have collected variables that represent proportions (i. e., the > proportion of sentences in a number of texts that belong to a certain > category). The distributions of these variables are highly skewed (the > proportions for most of the texts are zero or rather low). So my Low proportions, and a lot at zero? There is no way you can transform to "symmetry" when there is a clump at one end and a long tail at the other. First thought: the dichotomy of None/Some sometimes contains most of the information that is useful. Dummy Var1. Related thought: "none" is sometimes a separate dimension from what is implicitly measured by the continuous values above zero. If that dimension does seem useful: Dummy Var2. > question is: Is there a function that transforms the proportions into > symmetrically distributed variables? And is there a reliable statistics > text that discusses such transformations? "Symmetry" might happen, and it is good to have for the sake of testing. However, describing a scientific model with meaningful parameters is a better starting point, and you can devise tests from there. I mean: it is useful if you have a "Poisson model with a Poisson parameter", say, at the stage of setting up a model. You might want to take the square root before you do testing, and you know that is appropriate for the Poisson; but the raw Poisson parameter is a number that is ordinarily additive. I have not seen many texts that tackle transformations in the abstract. Finney's classic text on bioassay has a few pages. Or, I think, Mosteller and Tukey, "Data Analysis and Regression." -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html ================================================================= Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =================================================================
