The computer program PC-BILOG uses the
estimated posterior θ distribution to establish the
location and metric of the θ scale. This approach
to solving the identification problem has not been
examined extensively. Consequently, this study
investigated the equating of PC-BILOG results to an
underlying metric when a two-parameter IRT model
was used. The simulation results showed that the
means of the estimated item and θ parameters
generally were insensitive to characteristics of the
prior distribution on the item discriminations. The
finding of greatest interest was that the PC-BILOG
procedures preserved the variability of true θ distributions
having small variances while standardizing
the variability of those having large variances.
However, in both cases the results could be equated
to the true metric using existing techniques.
Index terms: ability metric, Bayesian estimation, BILOG,
equating, item response theory, prior distributions.