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Activity Number:
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198
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2007 : 2:00 PM to 3:50 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #309522 |
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Title:
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A Resampling-Based Approach To Test If a Model Provides Unbiased Parameter Estimates Under Various Missing Data Assumptions
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Author(s):
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Maria M. Sanchez*+ and Edmund Luo
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Companies:
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Merck & Co., Inc. and Merck & Co., Inc.
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Address:
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RY34 A316, Rahway, NJ, 07065,
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Keywords:
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Resampling Method
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Abstract:
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For the three well defined missing data mechanisms (i.e., MCAR, MAR and NMAR), unbiased parameter estimates could be obtained under MCAR and MAR as long as the underlying model accommodates the missing data assumptions. While it is impossible to test the assumptions of missing data, we propose a resampling based approach to test if the model accommodates the missing data assumptions via checking if it provides unbiased parameter estimates. The same technique can also be applied to test if a model provides unbiased parameter estimates by modeling the missing data mechanism for NMAR.
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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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