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Evaluating Statistical Targets for Assembling Parallel Mixed‐Format Test Forms
Author(s) -
Debeer Dries,
Ali Usama S.,
Rijn Peter W.
Publication year - 2017
Publication title -
journal of educational measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.917
H-Index - 47
eISSN - 1745-3984
pISSN - 0022-0655
DOI - 10.1111/jedm.12142
Subject(s) - polytomous rasch model , parallelism (grammar) , computer science , test (biology) , context (archaeology) , process (computing) , statistical hypothesis testing , item response theory , algorithm , data mining , statistics , mathematics , parallel computing , programming language , psychometrics , paleontology , biology
Test assembly is the process of selecting items from an item pool to form one or more new test forms. Often new test forms are constructed to be parallel with an existing (or an ideal) test. Within the context of item response theory, the test information function (TIF) or the test characteristic curve (TCC) are commonly used as statistical targets to obtain this parallelism. In a recent study, Ali and van Rijn proposed combining the TIF and TCC as statistical targets, rather than using only a single statistical target. In this article, we propose two new methods using this combined approach, and compare these methods with single statistical targets for the assembly of mixed‐format tests. In addition, we introduce new criteria to evaluate the parallelism of multiple forms. The results show that single statistical targets can be problematic, while the combined targets perform better, especially in situations with increasing numbers of polytomous items. Implications of using the combined target are discussed.