Regression assumptions in clinical psychology research practice - A systematic review of common misconceptions
- Published
- Accepted
- Subject Areas
- Psychiatry and Psychology, Statistics
- Keywords
- Linear Regression, Statistical Assumptions, Literature Review, Misconceptions about Normality
- Copyright
- © 2016 Ernst et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2016. Regression assumptions in clinical psychology research practice - A systematic review of common misconceptions. PeerJ Preprints 4:e2602v1 https://doi.org/10.7287/peerj.preprints.2602v1
Abstract
Misconceptions about the assumptions behind the standard linear regression model are widespread and dangerous. These lead to using linear regression when inappropriate, and to employing alternative procedures with less statistical power when unnecessary. Our systematic literature review investigated employment and reporting of assumption checks in twelve clinical psychology journals. The selected journals were representative based on impact factor. Findings indicate that normality of the variables themselves, rather than of the residuals, was wrongfully held for a necessary assumption in 4% of papers that use regression. Furthermore, 92% of all papers using linear regression were unclear about their assumption checks, violating APA-recommendations. This paper appeals for a heightened awareness for and increased transparency in the reporting of statistical assumption checking.
Author Comment
This is a submission to PeerJ for review.
Supplemental Information
Supplementary Material
This supplementary material outlines the individual classi cation for each of the papers analysed.