Analyzing heterogeneous treatment effects (HTEs) plays a crucial role in understanding the
impacts of educational interventions. A standard practice for HTE analysis is to examine …

Traditional measurement models assume that all item responses correlate with each other
only through their underlying latent variables. This conditional independence assumption …

The combination of network modeling and psychometric models has opened up exciting
directions of research. However, there has been confusion surrounding differences among …

The latent space item response model (LSIRM) is a newly-developed approach to analyzing
and visualizing conditional dependencies in item response data, manifested as the …

The homogeneity hypothesis is a common assumption in classic measurement. However,
the item response theory model assumes that different respondents with same ability have …

We study intelligence processes using a diffusion IRT model with random variability in
cognitive model parameters: variability in drift rate (the trend of information accumulation …

Personalized learning is the shaping of instruction to meet students' needs to support
student learning and improve learning outcomes. While it has received increasing attention …

This article aims to provide an overview of the potential advantages and utilities of the
recently proposed Latent Space Item Response Model (LSIRM) in the context of intelligence …

There recently have been many studies examining conditional dependence between
response accuracy and response times in cognitive tests. While most previous research has …

Statistical analysis of networks has gained increasing popularity in social and psychological
sciences. This study introduces a latent variable model for self-reported directional relations …