Comparison of four indirect (data mining) approaches to derive within-subject biological variation

• Published in: Clinical chemistry and laboratory medicine Vol. 60; no. 4; pp. 636 - 644
• Main Authors: Tan, Rui Zhen, Markus, Corey, Vasikaran, Samuel, Loh, Tze Ping
• Format: Journal Article
• Language: English
• Published: Germany De Gruyter 28.03.2022; Walter De Gruyter & Company
• Subjects: Biological variation; Coefficient of variation; Computer Simulation; Data Mining; Humans; indirect approach; Laboratories; Mathematical analysis; Median (statistics); outlier; Outliers (statistics); Parameters; Permutations; Populations; Reference Values; Research Design; Simulation; Variation; outlier; indirect approach; biological variation; data mining

Within-subject biological variation ( ) is a fundamental aspect of laboratory medicine, from interpretation of serial results, partitioning of reference intervals and setting analytical performance specifications. Four indirect (data mining) approaches in determination of were directly compared. Pai...