4 papers
Covariate-assisted Grade of Membership Models via Shared Latent Geometry
Zhiyu Xu, Yuqi Gu
The grade of membership model is a flexible latent variable model for analyzing multivariate categorical data through individual-level mixed membership scores. In many modern appli…
Valid and Efficient Two-Stage Latent Subgroup Analysis with Observational Data
Yuanhui Luo, Xinzhou Guo, Yuqi Gu
Subgroup analysis evaluates treatment effects across multiple sub-populations. When subgroups are defined by latent memberships inferred from imperfect measurements, the analysis t…
Spectral Clustering with Likelihood Refinement for High-dimensional Latent Class Recovery
Zhongyuan Lyu, Yuqi Gu
Latent class models are widely used for identifying unobserved subgroups from multivariate categorical data in social sciences, with binary data as a particularly popular example.…
Unfolding Tensors to Identify the Graph in Discrete Latent Bipartite Graphical Models
Yuqi Gu
We use a tensor unfolding technique to prove a new identifiability result for discrete bipartite graphical models, which have a bipartite graph between an observed and a latent lay…