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How Stable Are Top Choices Over Time? An Investigation Into Preferences Among Popular Baby Names In The United
Srinath Sampath1, Joseph S Verducci1
1Department of Statistics, The Ohio State University, 1958 Neil Avenue, 404 Cockins Hall, Columbus, OH 43210-1247.
Proceedings. American Statistical Association. Annual Meeting
|September 9, 2015
Summary
This study introduces a new method for assessing agreement between two rankings, offering a smooth estimator and a stopping rule. The approach effectively analyzes naming trends and sex-based differences in the US.
Area of Science:
- Statistics
- Data Analysis
Background:
- Assessing agreement between rankings is crucial for comparative studies.
- Existing models may lack smoothness or adaptability for differing item sets.
Purpose of the Study:
- To modify the Fligner and Verducci (1988) multistage model for improved ranking agreement assessment.
- To develop a locally smooth estimator and a stopping rule for agreement analysis.
- To extend the methodology for overlapping yet distinct item sets.
Main Methods:
- Modified Fligner and Verducci (1988) multistage model for rankings.
- Development of a locally smooth estimator of stage-wise agreement.
- Introduction of a stopping rule to determine the endpoint of agreement.
- Simulations to evaluate performance under various conditions.
Main Results:
- The modified model provides a locally smooth estimator for stage-wise agreement.
- An extension accommodates overlapping but different sets of items.
- A stopping rule effectively identifies the agreement endpoint.
- Simulations demonstrate strong performance across diverse scenarios.
Conclusions:
- The enhanced methodology offers a robust approach to assessing agreement in ranked data.
- Application to US newborn name data reveals insights into naming trends and sex-based conventions.
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