Journal article
A New Statistic to Assess Fitness of Cubic‐Spline Postsmoothing
Journal of educational measurement, Vol.57(1), pp.124-144
03/01/2020
DOI: 10.1111/jedm.12244
Abstract
In equating, smoothing techniques are frequently used to diminish sampling error. There are typically two types of smoothing: presmoothing and postsmoothing. For polynomial log‐linear presmoothing, an optimum smoothing degree can be determined statistically based on the Akaike information criterion or Chi‐square difference criterion. For cubic‐spline postsmoothing, visual inspection has been an important tool in choosing such optimum degrees in operational settings. This study introduces a new statistic for assessing the fitness of the cubic‐spline postsmoothing method, which accommodates three conditions: (1) one standard error band, (2) deviation from unsmoothed equivalents, and (3) smoothness. A principal advantage of the new statistic proposed in this study is that an optimum degree of smoothing can be selected automatically by giving consistent amount of attention to deviation and smoothness across multiple equatings, whereas visual inspection may not be consistent.
Details
- Title: Subtitle
- A New Statistic to Assess Fitness of Cubic‐Spline Postsmoothing
- Creators
- Hyung Jin Kim - University of IowaRobert L. Brennan - University of IowaWon‐Chan Lee - The University of Iowa
- Resource Type
- Journal article
- Publication Details
- Journal of educational measurement, Vol.57(1), pp.124-144
- Publisher
- Wiley
- DOI
- 10.1111/jedm.12244
- ISSN
- 0022-0655
- eISSN
- 1745-3984
- Number of pages
- 21
- Language
- English
- Date published
- 03/01/2020
- Academic Unit
- Center for Advanced Studies in Measurement and Assessment; Psychological and Quantitative Foundations
- Record Identifier
- 9984371109002771
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