This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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254
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Type:
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Contributed
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Date/Time:
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Monday, August 2, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #308533 |
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Title:
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Proportional Likelihood Ratio Model
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Author(s):
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Xiaodong Luo*+ and Wei Yann Tsai
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Companies:
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Mount Sinai School of Medicine and Columbia University
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Address:
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, , ,
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Keywords:
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Asymptotic properties ;
Biased sampling ;
Estimating equations ;
Semiparametric generalized linear models ;
Weighted distributions
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Abstract:
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We propose a semiparametric proportional likelihood ratio model which relates the covariates and the baseline density function. This model generalizes Gilbert-Lele-Vardi's selection bias model by allowing the weight function to depend on both covariates and outcomes, and extends the generalized linear models by leaving the distribution unspecified. Maximum likelihood estimator and moment-type estimators are proposed and their asymptotic properties are derived. A simulation study shows that the proposed estimators perform well compared with the gold-standard parametric maximum likelihood estimator.
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