Department of Statistics, Faculty of Science, 37848King Abdulaziz University, Jeddah, Saudi Arabia.
Ann Clin Biochem. 2021 Jul;58(4):377-383. doi: 10.1177/00045632211006453. Epub 2021 Apr 8.
The Spearman rank correlation test under classical statistics cannot be applied when the paired data is in interval or indeterminacy is presented in the paired data.
In this paper, the Spearman rank correlation test under neutrosophic statistics will be introduced. The proposed Spearman rank correlation test will be a generalization of the existing Spearman rank correlation test.
The proposed test is supposed to be more informative, flexible, and adequate to apply for the analysis of the measurement data. The application of the proposed test is given using the measurement of luteotropichormone data obtained from the clinical laboratory. Based on the information, the probability of accepting the null hypothesis is 0.95, the chance of committing a type-I error is 0.05 and the chance of indeterminacy about the acceptance of is 69%.
From the analysis, it is noted that the proposed test is more efficient in terms of the measure of indeterminacy as compared with the existing test. From the study, it is concluded that the proposed test is more informative, applicable and useable under an indeterminate environment as compared with the existing test under classical statistics. Therefore, it is recommended to apply the proposed test in clinical laboratories for testing the correlation between instruments.
当配对数据为区间数据或存在不确定性时，经典统计学中的斯皮尔曼等级相关检验无法应用。
本文将介绍基于 Neutrosophic 统计学的斯皮尔曼等级相关检验。所提出的斯皮尔曼等级相关检验是对现有斯皮尔曼等级相关检验的推广。
拟议的检验被认为更具信息量、更灵活、更适合应用于测量数据的分析。使用临床实验室获得的促黄体激素数据对提出的检验进行了应用。根据信息，接受零假设的概率为 0.95，犯第一类错误的概率为 0.05，接受 的不确定性的概率为 69%。
从分析中可以看出，与现有检验相比，所提出的检验在不确定性度量方面更有效。从研究中可以得出结论，与经典统计学下的现有检验相比，所提出的检验在不确定环境下更具信息量、适用性和可用性。因此，建议在临床实验室中应用该检验来检验仪器之间的相关性。
