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Activity Number: 699
Type: Contributed
Date/Time: Thursday, August 13, 2015 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract #316553
Title: Accurate Inference from Chemical Measurement Data Under the Rocke-Lorenzato Model
Author(s): Jian Zhao*
Companies: The EMMES Corporation
Keywords: Rocke and Lorenzato Model ; Higher order asymptotic ; Log-likelihood ratio statistic ; Coverage probability
Abstract:

Rocke and Lorenzato (1995) proposed a two-component model for measurement error for calibration analysis in analytical chemistry. Their analysis is likelihood based, and the coverage probabilities of the resulting confidence intervals are not always satisfactory, unless the sample sizes are large. In our research, higher order asymptotic procedures are used to obtain more accurate inferences when the sample sizes are small. An algorithm will be provided to implement our methodology. Numerical results and illustrative examples will be provided.

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

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