Efird Jimmy T
Cooperative Studies Program Coordinating Center, VA Boston, Lafayette City Center, 2 Avenue de Lafayette, Boston, MA 02111, USA.
Department of Radiation Oncology, School of Medicine, Case Western Reserve University, Cleveland, OH 44206, USA.
Medicina (Kaunas). 2024 Dec 22;60(12):2105. doi: 10.3390/medicina60122105.
This work represents a significant contribution to understanding the importance of appropriately rounding numbers with minimal error. That is, to reduce inexact rounding and data truncation error and simultaneously eliminate unintentional misleading findings in epidemiological studies. The rounding of numbers represents a compromise solution that attempts to find a balance between the loss of information from reporting too few significant digits versus retaining more digits than necessary. Substituting a rounded number for its original value may be acceptable and practical in many applied situations if an adequate degree of accuracy is retained. On the other hand, numeric error may result from improper rounding or data truncation which, in effect, compromises the credibility of study findings and may lead to a false sense of discovery. Performing complex computations on such values, especially when sequential or composite operations are involved, can lead to error propagation and inaccurate results. Having an overall awareness of the nature and impact of rounding error, including preventive actions, can contribute greatly to the integrity of research, yielding more reliable and accurate conclusions. Heuristic examples are provided to illustrate the consequences of rounding and data truncation error in epidemiology studies, specifically those pertaining to relative effect estimation.
这项工作对于理解以最小误差适当舍入数字的重要性做出了重大贡献。也就是说,减少不精确的舍入和数据截断误差,并同时消除流行病学研究中无意的误导性结果。数字的舍入是一种折衷解决方案,试图在因报告有效数字过少而导致的信息丢失与保留超过必要位数的数字之间找到平衡。如果保留了足够的准确度,在许多应用情况下用舍入后的数字代替其原始值可能是可以接受且实用的。另一方面,不当的舍入或数据截断可能会导致数值误差,实际上会损害研究结果的可信度,并可能导致错误的发现感。对这些值进行复杂计算,尤其是涉及顺序或复合运算时,可能会导致误差传播和不准确的结果。全面了解舍入误差的性质和影响,包括预防措施,对研究的完整性有很大帮助,能得出更可靠、准确的结论。文中提供了启发式示例来说明流行病学研究中舍入和数据截断误差的后果,特别是与相对效应估计相关的后果。