On 7 Jun 2002 06:58:54 -0700, [EMAIL PROTECTED] (Mobile Survey) wrote: > Rich Ulrich <[EMAIL PROTECTED]> wrote in message >news:<[EMAIL PROTECTED]>... > > I do most of my scale validating with Pearson correlations, > > which are the ones that people are most apt to understand.
> The problem with using the Pearson is not with the semantic > differential etc. My problem is with a dichotomous variable and one > ordinal variable.The rest of the variables I would treat as > continuous. So, what is the problem? You can apologize that the correlations are smaller because a dichotomy loses information compared to the original continuous variable - if there was one. A lot of so-called ordinal variables fare very well when you treat them as decently-distributed and continuous. And just do the regular tests and measures. If you *need* to keep the ordinal variable as 'ordinal' (you won't trust its metric, nor apply a simple transformation), then you could rank-transform that variable. What else do you think of? Dichotomize it? Document your work. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
