NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 7 results Save | Export
The Misidentified Identifiability Problem of Bayesian Knowledge Tracing
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Doroudi, Shayan; Brunskill, Emma – Grantee Submission, 2017
In this paper, we investigate two purported problems with Bayesian Knowledge Tracing (BKT), a popular statistical model of student learning: "identifiability" and "semantic model degeneracy." In 2007, Beck and Chang stated that BKT is susceptible to an "identifiability problem"--various models with different…
Descriptors: Bayesian Statistics, Research Problems, Statistical Analysis, Models
A Probabilistic Model of Visual Working Memory: Incorporating Higher Order Regularities into Working Memory Capacity Estimates
Peer reviewed Peer reviewed
Direct linkDirect link
Brady, Timothy F.; Tenenbaum, Joshua B. – Psychological Review, 2013
When remembering a real-world scene, people encode both detailed information about specific objects and higher order information like the overall gist of the scene. However, formal models of change detection, like those used to estimate visual working memory capacity, assume observers encode only a simple memory representation that includes no…
Descriptors: Short Term Memory, Visual Perception, Change, Identification
Using Loss Functions for DIF Detection: An Empirical Bayes Approach.
Peer reviewed Peer reviewed
Zwick, Rebecca; Thayer, Dorothy; Lewis, Charles – Journal of Educational and Behavioral Statistics, 2000
Studied a method for flagging differential item functioning (DIF) based on loss functions. Builds on earlier research that led to the development of an empirical Bayes enhancement to the Mantel-Haenszel DIF analysis. Tested the method through simulation and found its performance better than some commonly used DIF classification systems. (SLD)
Descriptors: Bayesian Statistics, Identification, Item Bias, Simulation
Identification of Learning Disabled Adolescents: A Bayesian Approach.
Peer reviewed Peer reviewed
Alley, Gordon R.; And Others – Learning Disability Quarterly, 1979
A method of identifying learning disabled adolescents using the method of Bayesian Revision of Subjective Probabilities, which utilizes both teacher judgments and psychometric tests, is proposed. (DB)
Descriptors: Bayesian Statistics, Check Lists, Identification, Learning Disabilities
On the Misuse of Manifest Variables in the Detection of Measurement Bias.
Peer reviewed Peer reviewed
Meredith, William; Millsap, Roger E. – Psychometrika, 1992
A unified treatment is presented for conditions that should allow detection of measurement bias using statistical procedures involving only observed or manifest variables. Computational results demonstrate that methods for studying bias that rely exclusively on manifest variables are not generally diagnostic of the presence or absence of…
Descriptors: Bayesian Statistics, Equations (Mathematics), Identification, Item Bias
Models of Integration Given Multiple Sources of Information.
Peer reviewed Peer reviewed
Massaro, Dominic W.; Friedman, Daniel – Psychological Review, 1990
Several models of information integration are developed and analyzed in the context of a prototypical pattern-recognition task. Evaluation, integration, and decision-making processes are specified for each. Simulations and predictions are carried out to provide a measure of identifiability or extent to which they can be distinguished from one…
Descriptors: Bayesian Statistics, Cognitive Processes, Criteria, Decision Making
An Investigation of Lord's Procedure for the Detection of Differential Item Functioning.
Peer reviewed Peer reviewed
Kim, Seock-Ho; And Others – Applied Psychological Measurement, 1994
Type I error rates of F. M. Lord's chi square test for differential item functioning were investigated using Monte Carlo simulations with marginal maximum likelihood estimation and marginal Bayesian estimation algorithms. Lord's chi square did not provide useful Type I error control for the three-parameter logistic model at these sample sizes.…
Descriptors: Algorithms, Bayesian Statistics, Chi Square, Error of Measurement