ERIC Number: EJ876713
Record Type: Journal
Publication Date: 2010
Abstractor: As Provided
Reference Count: 30
The Effects of Selection Strategies for Bivariate Loglinear Smoothing Models on NEAT Equating Functions
Moses, Tim; Holland, Paul W.
Journal of Educational Measurement, v47 n1 p76-91 Spr 2010
In this study, eight statistical strategies were evaluated for selecting the parameterizations of loglinear models for smoothing the bivariate test score distributions used in nonequivalent groups with anchor test (NEAT) equating. Four of the strategies were based on significance tests of chi-square statistics (Likelihood Ratio, Pearson, Freeman-Tukey, and Cressie-Read) and four additional strategies were based on different evaluations of the Likelihood Ratio Chi-Square statistic (Akaike Information Criterion, Bayesian Information Criterion, Consistent Akaike Information Criterion, and an index traced to Goodman). The focus was the implications of the selection strategies' selection tendencies for the accuracy of chained and poststratification equating functions. The results differentiated the strategies in terms of their tendencies to select models with particular bivariate parameterizations and the implications of these tendencies for equating bias and variability.
Descriptors: Equated Scores, Models, Statistical Distributions, Statistical Analysis, Scores, Tests, Criterion Referenced Tests, Evaluation
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Authoring Institution: N/A