This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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333
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Survey Research Methods
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Abstract - #306469 |
Title:
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Spline-Based Models for Prediction in Survey Samples
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Author(s):
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Hui Zheng*+
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Companies:
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Harvard Medical School
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Address:
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50 Staniford Street 5th floor, Suite 560, Boston, MA, 02114,
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Keywords:
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spline ;
pps sample ;
two-stage sample
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Abstract:
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In estimation of finite population quantities from survey samples, design-based methods focus on removing the bias while model-based methods seek to improve prediction of unobserved data.
Spline based models assume flexible mean functions and reduce the potential of model-misspecification, which is often considered a limitation by design-based statisticians. We have demonstrated that model-based method can shorten the confidence (or credible) intervals without sacrificing the coverage property, hence improve the inference quality. By incorporating design information in a spline model, one can achieve design-consistency without additional bias calibration.
I review spline-based methods proposed for various sampling designs including one-stage designs to multi-stage designs with clustered outcomes. I will discuss potential applications of the same philosophy to more complex situations.
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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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