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Two Approaches for Using Multiple Anchors in NEAT Equating: A Description and Demonstration.

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Title: Two Approaches for Using Multiple Anchors in NEAT Equating: A Description and Demonstration.
Authors: Tim Moses1 tmoses@ets.org, Weiling Deng1, Yu-Li Zhang1
Source: Applied Psychological Measurement. Jul2011, Vol. 35 Issue 5, p362-379. 18p.
Subject Terms: *Standardized tests, Equations, Missing data (Statistics), Multiple imputation (Statistics), Psychometrics
Abstract: Nonequivalent groups with anchor test (NEAT) equating functions that use a single anchor can have accuracy problems when the groups are extremely different and/or when the anchor weakly correlates with the tests being equated. Proposals have been made to address these issues by incorporating more than one anchor into NEAT equating functions. These proposals have not been extensively considered or comparatively evaluated. This study evaluates two proposed approaches for incorporating more than one anchor into NEAT equating functions, poststratification and missing data imputation. The approaches are studied and compared in an example of equating mixed format tests where the use of multiple equating is expected to improve equating. The results show that both approaches produced nearly equivalent equating results but that the poststratification approach has some flexibility and accuracy advantages over imputation in terms of standard errors. [ABSTRACT FROM AUTHOR]
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Database: Education Research Complete
Description
Abstract:Nonequivalent groups with anchor test (NEAT) equating functions that use a single anchor can have accuracy problems when the groups are extremely different and/or when the anchor weakly correlates with the tests being equated. Proposals have been made to address these issues by incorporating more than one anchor into NEAT equating functions. These proposals have not been extensively considered or comparatively evaluated. This study evaluates two proposed approaches for incorporating more than one anchor into NEAT equating functions, poststratification and missing data imputation. The approaches are studied and compared in an example of equating mixed format tests where the use of multiple equating is expected to improve equating. The results show that both approaches produced nearly equivalent equating results but that the poststratification approach has some flexibility and accuracy advantages over imputation in terms of standard errors. [ABSTRACT FROM AUTHOR]
ISSN:01466216
DOI:10.1177/0146621611405510