The major advantage of sequential classification, a technique for automatically classifying documents into previously selected categories, is that the entire document need not be processed before it is classified. This method assumes the availability of a priori categories, a selection of keywords representative of these categories, and the a…

In a situation where the population distribution of latent trait scores can be estimated, the ordinary maximum likelihood estimator of latent trait scores may be improved upon by taking the estimated population distribution into account. In this paper empirical Bayes estimators are compared with the liklihood estimator for three samples of 300…

A joint Bayesian estimation procedure for estimating parameters in the three-parameter logistic model is developed. Simulation studies show that the Bayesian procedure (1) ensures that the estimates stay in the parameter space and (2) produces better estimates than the joint maximum likelihood procedure. (Author/BS)

A general approach is proposed for modeling the structure of a r x s contingency table and for drawing marginal inferences about all parameters (e.g., interaction effects) in the model. The main approach is relevant whenever rs minus r minus s plus 1 is greater than or equal to 5. Military aptitude test data is used as illustration. (Author/LMO)

An alternative to the Rasch model is introduced. It characterizes strength of response according to the ratio of ability and difficulty parameters rather than their difference. Joint estimation and marginal estimation models are applied to two test data sets. (SLD)

Four bootstrap methods are identified for constructing confidence intervals for the binomial-error model. The extent to which similar results are obtained and the theoretical foundation of each method and its relevance and ranges of modeling the true score uncertainty are discussed. (SLD)

A procedure is introduced for determining the effect of testlet nonequivalence on operating characteristics of a testlet-based computerized mastery test (CMT). The procedure, which involves estimating the CMT decision rule twice with testlet likelihoods treated as equivalent or nonequivalent, is demonstrated with testlet pools from the Architect…

A theoretical framework for mastery testing based on item response theory and Bayesian decision theory is described and illustrated. Implementation depends on the availability of (1) a computerized test delivery system; (2) a pool of pretested items; and (3) a model relating observed test performance to true mastery status. (SLD)

Uses a flexible modeling strategy to examine the roles of measured ability, family characteristics, and proxies for secondary schooling quality as determinants of the decision to enter college. Finds that the link functions and estimated impacts of ability and family characteristics on the probabilities of enrolling in college are not constant…

This article proposes an item response theory (IRT) approach to constructing and scoring multidimensional pairwise preference items. Individual statements are administered and calibrated using a unidimensional single-stimulus model. Tests are created by combining multidimensional items with a small number of unidimensional pairings needed to…

This report describes new statistical procedures for item response analysis using estimation of item response curves used in mental testing with ability parameters treated as a random sample. Modern computer technology and the EM algorithm make this solution possible. The research focused on the theoretical formulation and solution of maximum…

A numerical procedure is outlined for obtaining an interval estimate of a parameter in an empirical Bayes estimation problem. The case where each observed value x has a binomial distribution, conditional on a parameter zeta, is the only case considered. For each x, the parameter estimated is the expected value of zeta given x. The main purpose is…

Assuming vectors of item responses depend on ability through a fully specified item response model, this paper presents maximum likelihood equations for estimating the population parameters without estimating an ability parameter for each subject. Asymptotic standard errors, tests of fit, computing approximations, and details of four special cases…

Presents a dynamic model of user behavior when scanning an information storage and retrieval system output list, compares rules for determining the user's optimum stopping point, presents an algorithm for implementing the Bayesian model, and discusses implications for retrieval system design. Provided are 13 figures and 15 references. (Author/RBF)