Brian W. Junker

Learn More
Multivariate categorical data, such as binary or multiple choice individual responses to a set of questions, are abundant in the social sciences. These data can be recorded in a multi-way contingency table, which quickly becomes sparse with any practical sample size when the number of questions goes up. Latent structure models, such as latent class and(More)
One of the major objections to the standard multiple-recapture approach to population estimation is the assumption of homogeneity of individual “capture” probabilities. Modeling individual capture heterogeneity is complicated by the fact that it shows up as as a restricted form of interaction between lists in the contingency table cross-classifying list(More)
We present methodology for developing functions that predict student scores on end of year state accountability exams from dynamic testing metrics developed from intelligent tutoring system log data. Our results confirm the findings of Heffernan et al. (2006) that online tutoring log based metrics provide better predictions than using paper and pencil(More)
An exploratory analysis of the Suicide Intent Scale was performed on a sample of 98 psychiatric inpatients who had made suicide attempts. The factor analysis was performed using a method for polychotomous data, and resulted in a two-factor solution. The Lethal Intent factor contained items pertaining to the subjective level of lethal intent, while the(More)
In recent years, as cognitive theories of learning and instruction have become richer, and computational methods to support assessment have become more powerful, there has been increasing pressure to make assessments truly criterion referenced, that is, to “report” on student achievement relative to theory-driven lists of examinee skills, beliefs and other(More)
"A central assumption in the standard capture-recapture approach to the estimation of the size of a closed population is the homogeneity of the 'capture' probabilities. In this article we develop an approach that allows for varying susceptibility to capture through individual parameters using a variant of the Rasch model from psychological measurement(More)
We give a historical introduction to item response theory, which places the work of Thurstone, Lord, Guttman and Coombs in a present-day perspective. The general assumptions of modern item response theory, local independence and monotonicity of response functions, are discussed, followed by a general framework for estimating item response models. Six(More)
can be found at: Applied Psychological Measurement Additional services and information for Email Alerts: Subscriptions: Reprints: Permissions:
In many testing situations, ordering the items by difficulty is helpful in analysing the testing data; examples include intelligence testing, analysis of differential item functioning, person-fit analysis, and exploring hypotheses about the order in which cognitive operations are acquired by children. In each situation, interpretation and analysis are made(More)