Title
Correcting unconditional parameter estimates in the Rasch model for inconsistency
Abstract
Results of simulation studies indicate that the unconditional
maximum likelihood method is commonly
regarded as an appropriate substitute for the theoretically
superior conditional method for estimating the
parameters of the Rasch model. To this end, the unconditional
estimates are "corrected" by a factor
(K - 1)/K, where 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 studies
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 estimation,
unconditional; One-parameter logistic model;
Rasch model.
Identifiers
other: doi:10.1177/014662168801200307
Previously Published Citation
Jansen, Paul G, Van den Wollenberg, Arnold L & Wierda, Folkert W. (1988). Correcting unconditional parameter estimates in the Rasch model for inconsistency. Applied Psychological Measurement, 12, 297-306. doi:10.1177/014662168801200307
Suggested Citation
Jansen, Paul G. W.; Van den Wollenberg, Arnold L.; Folkert W., Folkert W..
(1988).
Correcting unconditional parameter estimates in the Rasch model for inconsistency.
Retrieved from the University of Minnesota Digital Conservancy,
https://hdl.handle.net/11299/104298.