142 citations · 306 across the 18 of their papers we have counts for
19 papers
Generative AI in Publishing: An Editors' Panel on Ethics and Policies
Jun Yan, Mark Glickman, Paul S. Albert +3
Generative artificial intelligence (GenAI) is reshaping scholarly research faster than journals have developed stable norms for its use. This article presents an edited thematic ac…
A Simulation Study of the Performance of Statistical Models for Count Outcomes with Excessive Zeros
Zhengyang Zhou, Dateng Li, David Huh +2
Background: Outcome measures that are count variables with excessive zeros are common in health behaviors research. There is a lack of empirical data about the relative performance…
Approximate confidence distribution computing
Suzanne Thornton, Wentao Li, Minge Xie
Approximate confidence distribution computing (ACDC) offers a new take on the rapidly developing field of likelihood-free inference from within a frequentist framework. The appeal…
Divide-and-conquer methods for big data analysis
Xueying Chen, Jerry Q. Cheng, Min-ge Xie
In the context of big data analysis, the divide-and-conquer methodology refers to a multiple-step process: first splitting a data set into several smaller ones; then analyzing each…
Bridging Bayesian, frequentist and fiducial (BFF) inferences using confidence distribution
Suzanne Thornton, Minge Xie
Bayesian, frequentist and fiducial (BFF) inferences are much more congruous than they have been perceived historically in the scientific community (cf., Reid and Cox 2015; Kass 201…
Nonparametric fusion learning: synthesize inferences from diverse sources using depth confidence distribution
Dungang Liu, Regina Y. Liu, Minge Xie
Fusion learning refers to synthesizing inferences from multiple sources or studies to provide more effective inference and prediction than from any individual source or study alone…