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Activity Number: 603
Type: Contributed
Date/Time: Thursday, August 7, 2014 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract #312673
Title: Inter-Lab Calibration of Biomarker Data with Censoring
Author(s): Shizhe Chen*+ and Yunda Huang and Xiao-Hua Andrew Zhou
Companies: University of Washington and Fred Hutchinson Cancer Research Center and University of Washington
Keywords: Zero-inflated Data ; Calibration ; Asymptotic
Abstract:

Biomarker data are often collected from multiple laboratories. In addition, due to assay limitations some biomarker data may have a clump of zero-observations in a distribution of continuous non-negative responses where both the rate of positive responses and the response magnitude among responders are of interest. Differences in measurements between labs need to be accounted for when such biomarker data are compared or combined across-lab. We consider the problem of testing the means of such bivariate distributions of response rate and response magnitude between two independent samples, calibrated by paired-samples from the same laboratories. We propose a novel asymptotic test that operates on the calibrated data from a hurdle model. Our proposed method is compared to other tests commonly used in practice, including regression models and naïve method that ignores lab-differences. Simulation results under a variety of scenarios demonstrate satisfactory finite sample performance of the proposed test. We provide recommendations on situations to employ different methods and illustrate our methods using ELISpot assay data generated by two HIV vaccine labs.


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