EXPRESS: Clinical Laboratory Medicine Measurements Correlation Analysis under Uncertainty.

Aslam, Muhammad

BACKGROUND 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. METHODS 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. RESULTS 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 H_0N is 0.95, the chance of committing a type-I error is 0.05 and the chance of indeterminacy about the acceptance of H_0N is 69%. CONCLUSIONS From the analysis, it is noted that the proposed test is more efficient in terms of the measure of indeterminacy as compared to 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 to the existing test under classical statistics. Therefore, it is recommended to apply the proposed test in clinical laboratories for testing the correlation between instruments.