Optimal Bandwidth Selection in Observed-Score Kernel Equating

The selection of bandwidth in kernel equating is important because it has a direct impact on the equated test scores. The aim of this article is to examine the use of double smoothing when selecting bandwidths in kernel equating and to compare double smoothing with the commonly used penalty method....

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Bibliographic Details
Published in:Journal of educational measurement 2014-06, Vol.51 (2), p.201-211
Main Authors: Häggström, Jenny, Wiberg, Marie
Format: Article
Language:English
Subjects:
Admissions
Bandwidths
College admission
College admissions
College Entrance Examinations
Comparative Analysis
Data Analysis
Data collection
Data smoothing
Decision making models
Density estimation
Descriptive statistics
Entrance examinations
Equated Scores
Methods
Penalties
Penalty function
Performance evaluation
Signal bandwidth
Simulation
Simulations
Skewed distribution
Statistics
statistik
Test scores
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Summary:The selection of bandwidth in kernel equating is important because it has a direct impact on the equated test scores. The aim of this article is to examine the use of double smoothing when selecting bandwidths in kernel equating and to compare double smoothing with the commonly used penalty method. This comparison was made using both an equivalent groups design and a nonequivalent group with anchor test design. The performance of the methods was evaluated through simulation studies using both symmetric and skewed score distributions. In addition, the bandwidth selection methods were applied to real data from a college admissions test. The results show that the traditional penalty method works well although double smoothing is a viable alternative because it performs reasonably well compared to the traditional method.
ISSN:0022-0655
1745-3984
1745-3984
DOI:10.1111/jedm.12042