Hello all, I have a client who wants to compare the relationship/association of two variables (Y1 and Y2) between 2 groups (say Gender). They (statistically challenged) have left it to me to decide on method (and how to measure association).
Y1 and Y2 are ordinal, but are actually continuous variables binned into 0, .5, 1, 2 and 3. So, I'm o.k. with treating them as continuous. Anyways, here's what I'm thinking. 1) Fit a linear model Y1 = Y2 + Gender + Y2*Gender, and see if the interaction term is signficant. I figured the differences in slope would give me a decent comparison of the differences in association between Y1 and Y2, between the two groups. Keep in mind, I'm not wedded to actually comparing the Pearson correlation. Hence, 2) Use a Fisher's Z' Statistic to compare the Pearson Correlation. 3) Mantel-Haenszel is out 'cuz of sparse data. I've done 1) and 2) and they agree, insofar as the interaction term in 1) and the Z' Statistic in 2) are not signficant. Any opinions? I'm not too familiar with Fisher's Z' so don't know what it's quirks are (and AFAIK, couldn't find documentation in SAS for it, and very few Google hits). Thanks! ################################################# . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
