[EMAIL PROTECTED] (Paul R Swank) wrote in message news:<[EMAIL PROTECTED]>... > Paige is indeed correct. However, it is also true that the correlation > between two variables can be affected by distributional form. Did you > look to see if the distribution of the covariate was the same within > each level of the categorical variable that the covariate interacted > with? I suggest this only to help you understand your results. I always > feel uncomfortable when results vary depending on a transformation and > so wish to understand why. In fact, the best plan might be to run the > model both ways (transformed and untransformed covariate), output the > residuals and examine them by the grouping variable. > > Paul R. Swank, Ph.D. > Professor, Developmental Pediatrics > Medical School > UT Health Science Center at Houston > > > > -----Original Message----- > From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] > On Behalf Of Paige Miller > Sent: Tuesday, September 16, 2003 6:40 AM > To: [EMAIL PROTECTED] > Subject: Re: skewed covariate > > > 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/ . > ================================================================= > > . > . > ================================================================= > Instructions for joining and leaving this list, remarks about the > problem of INAPPROPRIATE MESSAGES, and archives are available at: > . http://jse.stat.ncsu.edu/ . > =================================================================
Have also just read that spss 11 uses the GLM approach to ancova - and that this adjusts for correlations between the DV and covariate - is this true? and if so is there any need to consider the interaction and test for homogeneity of regression slopes if using newer version of spss? thanx Emma . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
