We develop semiparametric Bayesian Thurstonian models for analyzing repeated choice decisions involving multinomial, multivariate binary or multivariate ordinal data. Our modeling framework has multiple components that together yield considerable flexibility in modeling preference utilities, cross-sectional heterogeneity and parameter-driven…

Over the course of instruction, instructors generally collect a great deal of information about each student. Integrating that information intelligently requires models for how a student's proficiency changes over time. Armed with such models, instructors can "filter" the data--more accurately estimate the student's current proficiency…

The Programme for International Student Assessment comparative study of reading performance among 15-year-olds is reanalyzed using statistical procedures that allow the full complexity of the data structures to be explored. The article extends existing multilevel factor analysis and structural equation models and shows how this can extract richer…

For much of the twentieth century, Markov theory and Markov processes have been widely accepted as valid ways to view statistical variables and parameters. In the complex realm of online searching, where researchers are always seeking the route to the best search strategies and the most powerful query terms and sequences, Markov process analysis…

Presents the dice game "Drop Dead" as an example of an absorbing Markov chain. Determines the expected length and expected score of a turn of the game. (ASK)

The Markov random graphs of O. Frank and D. Strauss (1986) and the estimation strategy for these models developed by Strauss and M. Ikeda (1990) are promising contributions. This paper describes a large class of models that can be used to investigate structure in social networks and illustrates their use. (SLD)

Developed an item response model for characterizing test-compromise that enables the estimation of item preview and score-gain distributions. In the approach, models parameters and posterior distributions are estimated by Markov Chain Monte Carlo procedures. Simulation study results suggest that when at least some test items are known to be…

After repeated associations between two events, E1 and E2, responses to E2 can be facilitated either because participants consciously expect E2 to occur after E1 or because E1 automatically activates the response to E2, or because of both. In this article, the authors report on 4 experiments designed to pit the influence of these 2 factors against…

This study examined the efficacy of an infrequently used statistical analysis in counselor education research. A Markov chain analysis was used to examine hypothesized differences between students' use of counseling skills in an introductory course. Thirty graduate students participated in the study. Independent raters identified the microskills…

Higher-order latent traits are proposed for specifying the joint distribution of binary attributes in models for cognitive diagnosis. This approach results in a parsimonious model for the joint distribution of a high-dimensional attribute vector that is natural in many situations when specific cognitive information is sought but a less informative…

This article proposes a practical method that capitalizes on the availability of information from multiple tests measuring correlated abilities given in a single test administration. By simultaneously estimating different abilities with the use of a hierarchical Bayesian framework, more precise estimates for each ability dimension are obtained.…

Bayesian network models offer a large degree of flexibility for modeling dependence among observables (item outcome variables) from the same task that may be dependent. This paper explores four design patterns for modeling locally dependent observations from the same task: (1) No context--Ignore dependence among observables; (2) Compensatory…

This study used a computerized simulation and problem-solving tool along with artificial neural networks (ANN) as pattern recognizers to identify the common types of strategies high school and college undergraduate chemistry students would use to solve qualitative chemistry problems. Participants were 134 high school chemistry students who used…

Considers the random sum SN+X1+X2+...+XN with a stopping rule N=min((n: SN absorbing Markov chain. (AIM)

Counselor ratings and statistical data from client files were gathered for 71 rehabilitation clients. A Markov Chain model was developed which provided viable probabilities for predicting rehabilitation outcome at three time periods, from 1 to 13 weeks after initial interview. Predictions generally followed a time progression toward stronger and…