Journal ArticleDOI
Estimating Multiple Classification Latent Class Models.
TLDR
Two algorithms for maximum likelihood (ML) and maximum a posteriori (MAP) estimation are described, which make use of the tractability of the complete data likelihood to maximize the observed data likelihood.Abstract:
This paper presents a new class of models for persons-by-items data. The essential new feature of this class is the representation of the persons: every person is represented by its membership tomultiple latent classes, each of which belongs to onelatent classification. The models can be considered as a formalization of the hypothesis that the responses come about in a process that involves the application of a number ofmental operations. Two algorithms for maximum likelihood (ML) and maximum a posteriori (MAP) estimation are described. They both make use of the tractability of the complete data likelihood to maximize the observed data likelihood. Properties of the MAP estimators (i.e., uniqueness and goodness-of-recovery) and the existence of asymptotic standard errors were examined in a simulation study. Then, one of these models is applied to the responses to a set of fraction addition problems. Finally, the models are compared to some related models in the literature.read more
Citations
More filters
Journal ArticleDOI
Cognitive Assessment Models with Few Assumptions, and Connections with Nonparametric Item Response Theory:
Brian W. Junker,Klaas Sijtsma +1 more
TL;DR: Some usability and interpretability issues for single-strategy cognitive assessment models are considered and an example shows that these models can be sensitive to cognitive attributes, even in data designed to well fit the Rasch model.
Journal ArticleDOI
The Generalized DINA Model Framework.
TL;DR: The G-DINA (generalized deterministic inputs, noisy “and” gate) model is a generalization of the DINA model with more relaxed assumptions and is equivalent to other general models for cognitive diagnosis based on alternative link functions.
Journal ArticleDOI
Higher-order latent trait models for cognitive diagnosis.
TL;DR: Higher-order latent traits are proposed for specifying the joint distribution of binary attributes in models for cognitive diagnosis, and a relatively simple model results, which is based on a plausible model for the relationship between general aptitude and specific knowledge.
Journal ArticleDOI
Measurement of psychological disorders using cognitive diagnosis models.
TL;DR: A new cognitive diagnosis model for use in psychological assessment is presented--the DINO (deterministic input; noisy "or" gate) model--which, as an illustrative example, is applied to evaluate and diagnose pathological gamblers.
Journal ArticleDOI
DINA Model and Parameter Estimation: A Didactic
TL;DR: This article focuses on one tractable and interpretable skills diagnosis model, the DINA model, and presents it didactically and discusses expectation-maximization and Markov chain Monte Carlo algorithms in estimating its model parameters.
References
More filters
Journal ArticleDOI
Maximum likelihood from incomplete data via the EM algorithm
Book
Bayesian Data Analysis
TL;DR: Detailed notes on Bayesian Computation Basics of Markov Chain Simulation, Regression Models, and Asymptotic Theorems are provided.
Book
Discrete multivariate analysis: theory and practice
TL;DR: Discrete Multivariate Analysis is a comprehensive text and general reference on the analysis of discrete multivariate data, particularly in the form of multidimensional tables, and contains a wealth of material on important topics.
Book
Introduction to the Theory of Statistics
TL;DR: In this article, a tabular summary of parametric families of distributions is presented, along with a parametric point estimation method and a nonparametric interval estimation method for point estimation.
Journal ArticleDOI
Introduction to the Theory of Statistics.
Jacob Wolfowitz,A. M. Mood +1 more
TL;DR: In this article, a tabular summary of parametric families of distributions is presented, along with a parametric point estimation method and a nonparametric interval estimation method for point estimation.
Related Papers (5)
Cognitive Assessment Models with Few Assumptions, and Connections with Nonparametric Item Response Theory:
Brian W. Junker,Klaas Sijtsma +1 more