This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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189
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Type:
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Invited
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Date/Time:
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Monday, August 2, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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ENAR
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Abstract - #308897 |
Title:
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Bayesian, Frequentist, or Both? Model-Robust Regression and the 'Sandwich' Estimator
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Author(s):
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Adam A. Szpiro*+ and Kenneth Rice and Thomas Lumley
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Companies:
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University of Washington and University of Washington and University of Washington
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Address:
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, , ,
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Keywords:
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Robust Regression ;
Estimating Equations ;
Sandwich Estimator ;
Bayesian Inference ;
Linear Regression
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Abstract:
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In applied analysis, it is often useful to estimate a linear trend in the data even though classical assumptions of linear regression (i.e., homoscedasticity and linear mean) do not hold. In the frequentist setting, estimating equations and the Huber-White sandwich covariance estimator give asymptotically valid inference, provided that sufficient care is taken to specify the target of inference and the covariate sampling frame. We present a new Bayesian approach that leads to uncertainty estimates with the same robustness properties as the sandwich estimator. Our derivation provides a compelling Bayesian justification for using this simple and popular tool, and it also clarifies what is being estimated when the data-generating mechanism is not linear. We demonstrate our approach using a simulation study and health care cost data from the Washington State Basic Health Plan.
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