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Abstract Details
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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 2, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #301334 |
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Title:
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Two-Sample Distribution-Free Inference Based on Partially Rank-Ordered Set Samples
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Author(s):
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Jinguo Gao *+ and Omer Ozturk
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Companies:
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The Ohio State University and The Ohio State University
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Address:
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Department of Statistics, Columbus, OH, 43210,
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Keywords:
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Imperfect ranking ;
Ranking models ;
Judgment subsets ;
Rank-sum-test ;
Pittman efficacy ;
Ranked set sampling
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Abstract:
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This paper develops distribution free inference for a location shift model based on a special sampling design. The new sampling design, in pincipal, is similar to a ranked set sampling with some clear differences. In the construction of the sample, a small set of experimental units are judgment ranked without measurement by allowing ties whenever the units can not be ranked with high confidence. These tied units are replaced in judgment subsets. The fully measured units are then selected from these partially ordered judgment subsets. Based on this sampling design, we construct an estimator, a test and a confidence interval for the location shift parameter. It is shown that the new sampling design is robust against any possible ranking error and has higher effciency than its competitor designs in the literature.
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Authors who are presenting talks have a * after their name.
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