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Activity Number:
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426
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Type:
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Contributed
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Date/Time:
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Wednesday, August 5, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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| Abstract - #304265 |
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Title:
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Goodness-of-Fit Tests for Archimedean Copula Models
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Author(s):
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Antai Wang*+
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Companies:
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Georgetown University
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Address:
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Building D, Suite 183, Washington, DC, 20057,
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Keywords:
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Archimedean Copula ; Multivariate Survival Analysis ; Multiple Imputation ; Fisher Transform
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Abstract:
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In this talk, we propose two tests for parametric models belonging to the Archimedean copula family, one for uncensored bivariate data and the other one for right censored bivariate data. Our test procedures are based upon the Fisher transform of the correlation coefficient of bivariate random vector $(U, V)$, which is a one-to-one transform of the original random pair $(T_{1}, T_{2})$ that can be modeled by an Archimedean copula model. Multiple imputation technique has been applied to establish our test for censored data and its $p$ value is computed by combing test statistics obtained from multiply imputed data sets. Simulation studies have shown that both procedures perform well when the sample size is large. The test for censored data has been demonstrated by a medical data example.
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- Authors who are presenting talks have a * after their name.
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