Ernst Anja F, Albers Casper J
Heymans Institute for Psychological Research, University of Groningen, Groningen, The Netherlands.
PeerJ. 2017 May 16;5:e3323. doi: 10.7717/peerj.3323. eCollection 2017.
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. Findings indicate that normality of the variables themselves, rather than of the errors, 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.
关于标准线性回归模型背后假设的误解广泛存在且十分危险。这些误解导致在不适当的时候使用线性回归,以及在不必要时采用统计功效较低的替代程序。我们的系统文献综述调查了12种临床心理学杂志中假设检验的使用和报告情况。研究结果表明,在4%使用回归分析的论文中,错误地将变量本身(而非误差)的正态性视为必要假设。此外,所有使用线性回归的论文中有92%对其假设检验情况不明确,违反了美国心理学会的建议。本文呼吁提高对统计假设检验报告的认识并增强透明度。