Online Program Home
  My Program

Abstract Details

Activity Number: 503 - SPAAC Poster Competition
Type: Topic Contributed
Date/Time: Wednesday, August 2, 2017 : 10:30 AM to 12:20 PM
Sponsor: Scientific and Public Affairs Advisory Committee
Abstract #324466
Title: Analysis of Data from Complex Chemical Experiments: Application of Bayesian Hierarchical Models
Author(s): Blaza Toman*
Companies: NIST
Keywords: uncertainty analysis ; measurement equation ; calibration

Chemical measurements obtained using liquid chromatography or other similar techniques are analyzed using a set of so-called measurement equations which relate the value being measured to various other variables, either measured, or partially known, based on properties of the measurement system such as calibration standards. In addition, the measurements are affected by various factors due to the experimental design. Thus the statistical analysis is necessarily quite complex. This presentation describes an analysis approach which incorporates the equations as well as the experimental factors in a Bayesian hierarchical model. The method is illustrated using measurements of 25-hydroxyvitamin D3 in solution reference materials via liquid chromatography with UV absorbance detection (LC-UV) and liquid chromatography mass spectrometric detection using isotope dilution (LC-IDMS).

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

Back to the full JSM 2017 program

Copyright © American Statistical Association