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Re: TRANSFORMATION OF IVS and DVs with reflection - multiple linear regression

Posted by Jon Peck on Nov 14, 2016; 2:20pm
URL: http://spssx-discussion.165.s1.nabble.com/TRANSFORMATION-OF-IVS-and-DVs-with-reflection-multiple-linear-regression-tp5733454p5733456.html

The normality assumption applies to the error terms, not the dependent variable.  So while transformations of the dependent variable may be appropriate, that does not follow from its nonnormality.

Second, you say that logistic regression would have been appropriate, but logistic is for a dichotomous variable, which would, of course, have a nonnormal distribution.  If that is what you have, then the transformations described do not make sense, and avoiding logistic or other similar methods is probably the wrong strategy.

On Mon, Nov 14, 2016 at 6:46 AM, researcher <[hidden email]> wrote:
I had a dataset with 7 IVs and the DV : wanted to use linear multiple linear
regression. The DV was very far from normal (accordion to usual tests). Very
positive skew so I used reflection and SQRT transformation and (to pleasant
surprise) the Dv then passed normality tests (p>.05). This was good but I
noticed that the direction of the relationship between one of the IVs and
the DV had changed - e.g. what had been a strongly positive beta (0.9) had
become approx -.0.9.

So I am wondering is it 'usual' to also transform the IVs when using this
sort of transformation on the DV?

Some other assumptions of MLR were met - no issues with multicollinearity,
heteroscascidicty

BTW I realise logistic regression would have been an option but there is a
small N (45) and larger samples are generally recommended with logistic.
Initial experiments with this gave a very large exp (B) for one IV but yet
was still not sig...

I am not a statistician -  I am a mixed methods researcher with some
experience in quantitative research so highly technical answers may well
blow over my head...

Any hekp appreciated though

Thanks





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Jon K Peck
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