Abstract
In the design of common-item equating, two groups of examinees are administered separate test forms, and each test form contains a common subset of items. We consider test equating under this situation as an incomplete data problem—that is, examinees have observed scores on one test form and missing scores on the other. Through the use of statistical data-imputation techniques, the missing scores can be replaced by reasonable estimates, and consequently the forms may be directly equated as if both forms were administered to both groups. In this paper we discuss different data-imputation techniques that are useful for equipercentile equating; we also use empirical data to evaluate the accuracy of these techniques as compared with chained equipercentile equating.
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Liou, M., Cheng, P.E. Equipercentile equating via data-imputation techniques. Psychometrika 60, 119–136 (1995). https://doi.org/10.1007/BF02294433
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DOI: https://doi.org/10.1007/BF02294433