Some Observations on the Metric of PC-BILOG Results
- 1 June 1990
- journal article
- Published by SAGE Publications in Applied Psychological Measurement
- Vol. 14 (2) , 139-150
- https://doi.org/10.1177/014662169001400203
Abstract
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 dis tributions having small variances while standardiz ing the variability of those having large variances. However, in both cases the results could be equat ed to the true metric using existing techniques.Keywords
This publication has 8 references indexed in Scilit:
- A Consumer's Guide to LOGIST and BILOGApplied Psychological Measurement, 1989
- Item Parameter Estimation Via Marginal Maximum Likelihood and an EM Algorithm: A DidacticJournal of Educational Statistics, 1988
- A Comparison of the Efficiency and Accuracy of BILOG and LOGISTPsychometrika, 1987
- Estimating Latent DistributionsPsychometrika, 1984
- Developing a Common Metric in Item Response TheoryApplied Psychological Measurement, 1983
- Marginal Maximum Likelihood Estimation of Item Parameters: Application of an EM AlgorithmPsychometrika, 1981
- SOLVING MEASUREMENT PROBLEMS WITH THE RASCH MODELJournal of Educational Measurement, 1977
- CONDITIONAL INFERENCE FOR MULTIPLE‐CHOICE QUESTIONNAIRESBritish Journal of Mathematical and Statistical Psychology, 1973