Posted by
Rudobeck, Emil (LLU) on
Nov 22, 2016; 4:57am
URL: http://spssx-discussion.165.s1.nabble.com/TRANSFORMATION-OF-IVS-and-DVs-with-reflection-multiple-linear-regression-tp5733454p5733497.html
As a side note, consider that transformation might not be necessary. Many people jump to non-parametric tests or transformations right away, but regression is actually robust to violations of normality and even if normality is violated, the regression coefficients will remain unbiased (but not the significance). The issue with normality can also be overcome with bootstrapping. There are additional options like robust regression (through the R plug-in).
As far as interpretation of coefficients is concerned, you can back-transform your coefficients after most types of transformations. The caveat is that you can't back-transform SEs, only CIs.
This is a helpful paper about assumptions of regression: Williams MN, Grajales CAG, Kurkiewicz D (2013) Assumptions of multiple regression: correcting two misconceptions. Practical Assessment, Research & Evaluation 18:2.
http://pareonline.net/getvn.asp?v=18&n=11________________________________________
From: SPSSX(r) Discussion [
[hidden email]] on behalf of researcher [
[hidden email]]
Sent: Monday, November 14, 2016 3:48 PM
To:
[hidden email]
Subject: Re: TRANSFORMATION OF IVS and DVs with reflection - multiple linear regression
Bruce I appreciate your help but if you read my posts it is clear that I am
asking about multiple linear regression and only mentioned logistic in
passing (as something that I had considered but rejected). I agree I could
have said more about the variables etc but time was short, on a deadline,
and I did not think it was that relevant for the problem. I do appreciate
the expertise available in this group but in this case was just after a
'quick and dirty' solution for want of a better term.
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