Abstract Details
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Activity Number:
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41
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Type:
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Contributed
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Date/Time:
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Sunday, August 4, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #307557 |
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Title:
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How Stable Are Top Choices Over Time? An Investigation into Preferences Among Popular Baby Names in the United States
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Author(s):
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Srinath Sampath*+ and Joseph S Verducci
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Companies:
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The Ohio State University and The Ohio State University
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Keywords:
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partial rankings ;
top-K rank list ;
multistage model ;
maximum likelihood estimation ;
stopping rule ;
consensus
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Abstract:
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For the problem of assessing initial agreement between two rankings of long lists, inference in the Fligner and Verducci (1988) multistage model for rankings is modified to provide a locally smooth estimator of stage-wise agreement. An extension to the case of overlapping but different sets of items in the two lists, and a stopping rule to identify the endpoint of agreement, are also provided. Simulations show that this approach performs very well under several conditions. The methodology is applied to a database of popular names for newborns in the United States and provides insights into trends as well as differences in naming conventions between the two sexes.
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Authors who are presenting talks have a * after their name.
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