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Activity Number:
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219
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2003 : 9:00 AM to 10:50 AM
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Sponsor:
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WNAR
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| Abstract - #302257 |
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Title:
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Generalized Estimating Equations for Biomarker-Based Exposure Estimation
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Author(s):
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Scott Michael Bartell*+ and Wesley Orin Johnson
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Companies:
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University of California, Davis and University of California
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Address:
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Dept. of Statistics, Davis, CA, 95616-1842,
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Keywords:
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Abstract:
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Biomarker measurements such as blood lead concentrations and hair mercury concentrations are often used to make inferences about previous rates of toxicant intake. Exposure rates are typically estimated using a "steady state" assumption. However, toxicant exposures are typically episodic and vary in magnitude over time, violating the steady-state model. Treating each biomarker measurement as linear combination of previous daily exposure magnitudes is a simple but reasonable toxicokinetic model for many situations. When exposure patterns are intermittent each daily exposure magnitude is described by a mixture distribution with a probability mass at zero and some continuous density over a range of positive values, and each biomarker measurement involves a convolution of differentially weighted mixture distributions. Likelihood functions are difficult to obtain in this setting, but generalized estimating equations can be applied successfully. We present the general approach and demonstrate the method using blood mercury measurements.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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