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[HTML][HTML] Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions
Accounting for some types of heterogeneity has been an important pathway to improving our
models in the transportation domain, specifically in travel behavior research. This study …
models in the transportation domain, specifically in travel behavior research. This study …
Statistical applications to cognitive diagnostic testing
Diagnostic classification tests are designed to assess examinees' discrete mastery status on
a set of skills or attributes. Such tests have gained increasing attention in educational and …
a set of skills or attributes. Such tests have gained increasing attention in educational and …
Item Response Theory--A Statistical Framework for Educational and Psychological Measurement
Item response theory (IRT) has become one of the most popular statistical models for
psychometrics, a field of study concerned with the theory and techniques of psychological …
psychometrics, a field of study concerned with the theory and techniques of psychological …
Sufficient and necessary conditions for the identifiability of the Q-matrix
Restricted latent class models (RLCMs) have recently gained prominence in educational
assessment, psychiatric evaluation, and medical diagnosis. In contrast to conventional latent …
assessment, psychiatric evaluation, and medical diagnosis. In contrast to conventional latent …
Diagnostic classification analysis of problem-solving competence using process data: An item expansion method
Process data refer to data recorded in computer-based assessments (CBAs) that reflect
respondents' problem-solving processes and provide greater insight into how respondents …
respondents' problem-solving processes and provide greater insight into how respondents …
New paradigm of identifiable general-response cognitive diagnostic models: beyond categorical data
Cognitive diagnostic models (CDMs) are a popular family of discrete latent variable models
that model students' mastery or deficiency of multiple fine-grained skills. CDMs have been …
that model students' mastery or deficiency of multiple fine-grained skills. CDMs have been …
Learning attribute hierarchies from data: Two exploratory approaches
In cognitive diagnostic assessment, multiple fine-grained attributes are measured
simultaneously. Attribute hierarchies are considered important structural features of …
simultaneously. Attribute hierarchies are considered important structural features of …
A Gibbs sampling algorithm with monotonicity constraints for diagnostic classification models
Diagnostic classification models (DCMs) are restricted latent class models with a set of cross-
class equality constraints and additional monotonicity constraints on their item parameters …
class equality constraints and additional monotonicity constraints on their item parameters …
Exploratory Restricted Latent Class Models with Monotonicity Requirements under Pòlya—gamma Data Augmentation
Restricted latent class models (RLCMs) provide an important framework for supporting
diagnostic research in education and psychology. Recent research proposed fully …
diagnostic research in education and psychology. Recent research proposed fully …
Bayesian pyramids: Identifiable multilayer discrete latent structure models for discrete data
High-dimensional categorical data are routinely collected in biomedical and social sciences.
It is of great importance to build interpretable parsimonious models that perform dimension …
It is of great importance to build interpretable parsimonious models that perform dimension …