Online Program Home
  My Program

Abstract Details

Activity Number: 669 - Recent Advances in Nonparametric Statistics
Type: Contributed
Date/Time: Thursday, August 3, 2017 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract #324331 View Presentation
Title: Multivariate Nonparametric Tolerance Regions for Determining Reference Regions in Laboratory Medicine
Author(s): Derek Young* and Thomas Mathew
Companies: University of Kentucky and University of Maryland, Baltimore County
Keywords: coverage probability ; data depth ; order statistics ; reference regions ; tolerance regions

Reference regions are widely used in clinical chemistry and laboratory medicine to interpret the results of biochemical or physiological tests of patients. There are well-established methods in the literature for reference limits for univariate measurements, however, only limited methods are available for the construction of multivariate reference regions. This is because traditional multivariate statistical regions (e.g., confidence, prediction, and tolerance regions) are not constructed based on a hyperrectangular geometry. We address this problem by developing multivariate hyperrectangular nonparametric tolerance regions for setting the reference regions. Our approach uses statistical data depth to determine which points to trim and then the extremes of the trimmed dataset are used as the faces of the hyperrectangular region. We also specify the number of points to trim based on previously-established asymptotic results. An extensive coverage study shows the favorable performance of our algorithm for moderate to large sample sizes. We apply our procedure to a healthy reference sample to obtain reference regions for three analytes pertaining to kidney function.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2017 program

Copyright © American Statistical Association