Item Calibration in Incomplete Testing Designs
Door: Eggen, Th.J.H.M., Verhelst, N.D. | 01-03-1992 The paper discusses the justifiability of item parameter estimation in incomplete testing designs in item response theory.Marginal maximum likelihood (MML) as well as conditional maximum likelihood (CML) procedures are considered in three commonly used incomplete designs: random incomplete, multistage testing and targeted testing designs. It is shown that in these designs the justifiability of MML can be deduced from Rubin's (1976) general theory on inference in the presence of missing data. In CML this is not possible and the justification
can be established from the S-ancillarity condition of the neglected part of the likelihood. Incorrect uses of standard MML- and CML-algorithms are discussed.
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