Exploiting Auxiliary Infornlation About Examinees in the Estimation of Item Parameters
- 1 March 1987
- journal article
- Published by SAGE Publications in Applied Psychological Measurement
- Vol. 11 (1) , 81-91
- https://doi.org/10.1177/014662168701100106
Abstract
The precision of item parameter estimates can be increased by taking advantage of dependencies be tween the latent proficiency variable and auxiliary ex aminee variables such as age, courses taken, and years of schooling. Gains roughly equivalent to two to six additional item responses can be expected in typical educational and psychological applications. Empirical Bayesian computational procedures are presented and illustrated with data from the National Assessment of Educational Progress survey.Keywords
This publication has 8 references indexed in Scilit:
- Bayes Modal Estimation in Item Response ModelsPsychometrika, 1986
- Estimation of Latent Group EffectsJournal of the American Statistical Association, 1985
- Estimating Latent DistributionsPsychometrika, 1984
- Parameter Estimation in Latent Trait ModelsPsychometrika, 1983
- Finding the Observed Information Matrix When Using the EM AlgorithmJournal of the Royal Statistical Society Series B: Statistical Methodology, 1982
- Marginal Maximum Likelihood Estimation of Item Parameters: Application of an EM AlgorithmPsychometrika, 1981
- Maximum Likelihood from Incomplete Data Via the EM AlgorithmJournal of the Royal Statistical Society Series B: Statistical Methodology, 1977
- Bayes Estimates for the Linear ModelJournal of the Royal Statistical Society Series B: Statistical Methodology, 1972