Janszky Imre, Bjørngaard Johan Håkon, Romundstad Pål, Vatten Lars, Orsini Nicola
Deparment of Public Health, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway,
Department of Public Health Sciences, Karolinska Insitutet, Stockholm, Sweden.
Clin Epidemiol. 2019 Jan 23;11:127-132. doi: 10.2147/CLEP.S184231. eCollection 2019.
Currently used methods to express random error are often misinterpreted and consequently misused by biomedical researchers. Previously we proposed a simple approach to quantify the amount of random error in epidemiological studies using OR for binary exposures. Expressing random error with the number of random error units (REU) does not require solid background in statistics for a proper interpretation and cannot be misused for making oversimplistic interpretations relying on statistical significance. We now expand the use of REU to the most common measures of associations in epidemiology and to continuous variables, and we have developed a Stata program, which greatly facilitates the calculation of REU.
目前用于表达随机误差的方法常常被生物医学研究人员误解,进而被误用。此前我们提出了一种简单的方法,用于在流行病学研究中使用比值比(OR)对二元暴露的随机误差量进行量化。用随机误差单位(REU)的数量来表达随机误差,对于正确解读而言不需要坚实的统计学背景知识,并且不会因依赖统计学显著性而被滥用于做出过于简单化的解读。我们现在将REU的应用扩展到流行病学中最常见的关联度量以及连续变量,并开发了一个Stata程序,这极大地便利了REU的计算。