Correcting Unconditional Parameter Estimates in the Rasch Model for Inconsistency

Publisher Website
Google Scholar
Abstract
Results of simulation studies indicate that the un conditional maximum likelihood method is commonly regarded as an appropriate substitute for the theoreti cally superior conditional method for estimating the parameters of the Rasch model. To this end, the un conditional estimates are "corrected" by a factor (K — 1)/K, where K is the number of items. In this paper, the simulation study of Wright and Douglas (1977b), which seemed to corroborate this correction term, is critically discussed. It appears to contain a puzzling assumption, and to rest on inadequate logic. Accordingly, there is a need for new simulation stud ies on the validity of the correction term (K — 1)/K for unconditional maximum likelihood estimation in the Rasch model. Index terms: Item response theory, item parameter estimation; Item response theory, one- parameter logistic model; Maximum likelihood estima tion, unconditional; One-parameter logistic model; Rasch model.