ERIC Number: EJ1198335
Record Type: Journal
Publication Date: 2018
Pages: 18
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0022-0655
EISSN: N/A
A Comparison of Strategies for Smoothing Parameter Selection for Mixed-Format Tests under the Random Groups Design
Liu, Chunyan; Kolen, Michael J.
Journal of Educational Measurement, v55 n4 p564-581 Win 2018
Smoothing techniques are designed to improve the accuracy of equating functions. The main purpose of this study is to compare seven model selection strategies for choosing the smoothing parameter (C) for polynomial loglinear presmoothing and one procedure for model selection in cubic spline postsmoothing for mixed-format pseudo tests under the random groups design. These model selection strategies were compared for four sample sizes (500, 1,000, 2,000, and 3,000) and two content areas (Advanced Placement [AP] Biology and AP Environmental Science). For polynomial loglinear presmoothing, the Akaike information criterion (AIC) was the only statistic that reduced both random equating error and total equating error in all investigated conditions. Cubic spline postsmoothing tended to produce more accurate results than any of the model selection strategies in polynomial loglinear smoothing.
Descriptors: Comparative Analysis, Accuracy, Models, Sample Size, Advanced Placement, Biology, Science Tests, Environmental Education, Science Education, Error of Measurement, Test Format
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A