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Activity Number:
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274
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2008 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #301681 |
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Title:
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Inference on Quantile Regression for Heteroscedastic Mixed Models
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Author(s):
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Huixia Wang*+
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Companies:
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North Carolina State University
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Address:
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2501 Founders Drive, 209F Patterson Hall, Raleigh, NC, 27695,
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Keywords:
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Apnea duration ; Estimating equation ; Longitudinal data ; Rank score test ; Weighted quantile regression
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Abstract:
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This paper develops two weighted quantile rank score tests for the significance of fixed effects in a class of mixed models with nonhomogeneous groups. One test is constructed by simply weighting the residuals to account for heteroscedasticity, while the other test is based on asymptotically optimal weights accounting for both heteroscedasticity and correlation. Without appropriate weights to account for heteroscedasticity, the quantile rank score tests often perform poorly. In finite samples, the test with optimal weights tends to provide marginal improvements over the one with simpler weights unless the intra-subject correlation is extremely high. We illustrate the value of the proposed methods by modeling several quantiles of the apnea duration of elderly during normal swallowing.
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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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