1 citations · 3 across the 4 of their papers we have counts for
6 papers
Dynamic Survival Transformers for Causal Inference with Electronic Health Records
Prayag Chatha, Yixin Wang, Zhenke Wu +1
In medicine, researchers often seek to infer the effects of a given treatment on patients' outcomes. However, the standard methods for causal survival analysis make simplistic assu…
baker: An R package for Nested Partially-Latent Class Models
Irena B Chen, Qiyuan Shi, Scott L Zeger +1
This paper describes and illustrates the functionality of the baker R package. The package estimates a suite of nested partially-latent class models (NPLCM) for multivariate binary…
Dynamic statistical inference in massive datastreams
Jingshen Wang, Lilun Du, Changliang Zou +1
Modern technological advances have expanded the scope of applications requiring analysis of large-scale datastreams that comprise multiple indefinitely long time series. There is a…
A Robust Functional EM Algorithm for Incomplete Panel Count Data
Alexander Moreno, Zhenke Wu, Jamie Yap +5
Panel count data describes aggregated counts of recurrent events observed at discrete time points. To understand dynamics of health behaviors, the field of quantitative behavioral…
Regression Analysis of Dependent Binary Data for Estimating Disease Etiology from Case-Control Studies
Zhenke Wu, Irena Chen
In large-scale disease etiology studies, epidemiologists often need to use multiple binary measures of unobserved causes of disease that are not perfectly sensitive or specific to…
A Bayesian Approach to Restricted Latent Class Models for Scientifically-Structured Clustering of Multivariate Binary Outcomes
Zhenke Wu, Livia Casciola-Rosen, Antony Rosen +1
In this paper, we propose a general framework for combining evidence of varying quality to estimate underlying binary latent variables in the presence of restrictions imposed to re…