Iterative Outlier Removal: A Method for Identifying Outliers in Laboratory Recalibration Studies.

ABSTRACT:

Background

Extreme values that arise for any reason, including those through nonlaboratory measurement procedure-related processes (inadequate mixing, evaporation, mislabeling), lead to outliers and inflate errors in recalibration studies. We present an approach termed iterative outlier removal (IOR) for identifying such outliers.

Methods

We previously identified substantial laboratory drift in uric acid measurements in the Atherosclerosis Risk in Communities (ARIC) Study over time. Serum uric acid was originally measured in 1990-1992 on a Coulter DACOS instrument using an uricase-based measurement procedure. To recalibrate previous measured concentrations to a newer enzymatic colorimetric measurement procedure, uric acid was remeasured in 200 participants from stored plasma

SUBMITTER: Parrinello CM 

PROVIDER: S-EPMC4927349 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature