Some Properties of a Bayesian Adaptive Ability Testing Strategy.
Abstract
Four monte carlo simulation studies of Owen's Bayesian sequential procedure for adaptive mental testing were conducted. Whereas previous simulation studies have concentrated on evaluating it in terms of the correlation of its test scores with simulated ability in a normal population, these studies explored additional properties, both in a normally distributed population and in a distribution-free context. Study 1 replicated previous studies with finite item pools, but examined such properties as the bias of estimate, mean absolute error, and correlation of test length with ability. Studies 2 and 3 examined the same variables in a number of hypothetical infinite item pools, investigating the effects of item discriminating power, guessing, and variable vs. fixed test length. Study 4 investigated some properties of the Bayesian test scores as latent trait estimators, under three different configurations (regressions of item discrimination on item difficulty) of item pools. The study results indicate that the ability estimates derived from the Bayesian test strategy were highly correlated with ability level. However, the ability estimates were also highly correlated with number of items administered, were non-linearly biased and provided measurements which were not of equal precision at all levels of ability.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1974
- Accession Number
- ADA022964
Entities
People
- David J. Weiss
- James R McBride
Organizations
- University of Minnesota