emma wrote: > Hi there, > > Am new to posting - so let me know if haven't included enough info etc. > > I have conducted an ancova with two between subjects (group - 3 > levels) and education (2 levels) IV's and one covariate. The DV has > been transformed using sq root. When I run the analysis I have an > interaction between group and the covariate suggesting a lack of > homogeneity of regression slopes. In trying to understand the > interaction (which was unexpected) - I ran some diagnostic tests on > the covariate which I found to be skewed. I decided to transform the > covariate (using sq root in line with the DV) - and this normalised > the distribution. When re-running the ancova using both of the transformed > variables the interaction disappeared. Is this valid? Is it > necessary to transform a covariate if: 1) it is non-normally > distributed and/or 2) to be consistent with the DV? I should probably > mention that although I have homogeneity of variance the sample sizes > are small and unequal (46/15/15).
The standard assumption in fitting Linear Models is that the DV errors are normally distributed, and NOT that the covariate itself is normally distributed. The covariate can have any distribution, as long as the DV errors are normally distributed. Transforming the IVs can indeed change the presense or absence of an interaction. -- Paige Miller Eastman Kodak Company [EMAIL PROTECTED] http://www.kodak.com "It's nothing until I call it!" -- Bill Klem, NL Umpire "When you get the choice to sit it out or dance, I hope you dance" -- Lee Ann Womack . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
