6 papers
Sparse Latent Class Analysis: Post-Estimation Refinement via Item-level Pseudo-Likelihood
Yuxuan Xu, Lea Kaufmann, Yunxiao Chen +2
Latent Class Analysis (LCA) is widely used to identify unobserved subgroups in social and behavioural sciences. A long-standing challenge for LCA is the interpretability of the lat…
A Generalized Additive Partial-Mastery Cognitive Diagnosis Model
Camilo Cárdenas-Hurtado, Sze Ming Lee, Yunxiao Chen +1
Cognitive diagnosis models (CDMs) are restricted latent class models widely used to measure attributes of interest in diagnostic assessments across education, psychology, biomedica…
Maximum softly penalised likelihood in factor analysis
Philipp Sterzinger, Ioannis Kosmids, Irini Moustaki
Estimation in exploratory factor analysis often yields estimates on the boundary of the parameter space. Such occurrences, known as Heywood cases, are characterised by non-positive…
Boosting Stochastic Optimisation for High-dimensional Latent Variable Models
Motonori Oka, Yunxiao Chen, Irini Moustaki
Latent variable models are widely used in social and behavioural sciences, including education, psychology, and political science. With the increasing availability of large and com…
When Composite Likelihood Meets Stochastic Approximation
Giuseppe Alfonzetti, Ruggero Bellio, Yunxiao Chen +1
A composite likelihood is an inference function derived by multiplying a set of likelihood components. This approach provides a flexible framework for drawing inference when the li…
Unfolding the Network of Peer Grades: A Latent Variable Approach
Giuseppe Mignemi, Yunxiao Chen, Irini Moustaki
Peer grading is an educational system in which students assess each other's work. It is commonly applied under Massive Open Online Course (MOOC) and offline classroom settings. Wit…