Abstract
A set of linear conditions on item response functions is derived that guarantees identical observed-score distributions on two test forms. The conditions can be added as constraints to a linear programming model for test assembly that assembles a new test form to have an observed-score distribution optimally equated to the distribution on an old form. For a well-designed item pool and items fitting the IRT model, use of the model results into observed-score pre-equating and prevents the necessity ofpost hoc equating by a conventional observed-score equating method. An empirical example illustrates the use of the model for an item pool from the Law School Admission Test.
Original language | English |
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Pages (from-to) | 401-418 |
Number of pages | 17 |
Journal | Psychometrika |
Volume | 63 |
Issue number | 4 |
DOIs | |
Publication status | Published - 1998 |
Keywords
- Item response theory (IRT)
- Test equating
- Test assembly
- generalized binomial distribution
- 0–1 linear programming