Department of Biomedical, Industrial & Human Factors Engineering, Wright State University, Dayton, Ohio 45435-0001, USA.
Ergonomics. 2009 May;52(5):499-511. doi: 10.1080/00140130802392999.
This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.
本文旨在展示测量误差对人机工程学研究中心理测量的影响。人机工程学研究中,多种来源都可能导致随机测量误差,这些误差几乎可以扭曲所有计算出的统计数据,并导致研究人员得出错误的结论。本文讨论并说明了测量误差对五种最常用的统计分析工具的影响:相关分析;方差分析;线性回归;因子分析;线性判别分析。结果表明,测量误差会大大削弱变量之间的相关性,降低方差分析的统计功效,扭曲(高估、低估甚至改变符号)回归系数,低估因子分析中最重要因素的解释贡献,降低判别分析中判别函数和个别变量判别能力的显著性。讨论将仅限于主观量表和调查方法及其可靠性估计。人机工程学研究中应用的其他方法,如物理和生理测量以及化学和生物医学分析方法,也存在测量误差问题,但这超出了本文的范围。由于人们对人机工程学研究中理论的发展和检验越来越感兴趣,因此了解测量误差对其实验结果的影响对于人机工程学研究人员来说变得非常重要,作者认为这对于理论发展和人机工程学领域的知识积累的研究进展至关重要。