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Found 5 papers, 1 papers with code
Identifiability of Bifactor Models
The bifactor model and its extensions are multidimensional latent variable models, under which each item measures up to one subdimension on top of the primary dimension(s).
Statistics Theory Applications Statistics Theory
Subtask Analysis of Process Data Through a Predictive Model
Response process data collected from human-computer interactive items contain rich information about respondents' behavioral patterns and cognitive processes.
ProcData: An R Package for Process Data Analysis
In addition, several response process generators and a real dataset of response processes of the climate control item in the 2012 Programme for International Student Assessment are included in the package.
An Exploratory Analysis of the Latent Structure of Process Data via Action Sequence Autoencoder
In this article, we propose a method to extract latent variables from process data.
Likelihood Adaptively Modified Penalties
A new family of penalty functions, adaptive to likelihood, is introduced for model selection in general regression models.
