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20222026
most citedApproximating Partial Likelihood Estimators via Optimal Subsampling

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ME2026

Efficient Poisson Subsampling for the Partially Linear Additive Cox Model

Dongxiao Han, Liuquan Sun, Chunjie Wang +3

To address the computational and storage challenges often encountered in large-scale survival data analysis, we propose an efficient Poisson subsampling method for the partially li…

stat.CO2023

A Framework for Mediation Analysis with Massive Data

Haixiang Zhang, Xin Li

During the past few years, mediation analysis has gained increasing popularity across various research fields. The primary objective of mediation analysis is to examine the direct…

stat.ME2023

Efficient Adjusted Joint Significance Test and Sobel-Type Confidence Interval for Mediation Effect

Haixiang Zhang

Mediation analysis is an important statistical tool in many research fields, where the joint significance test is widely utilized for examining mediation effects. Nevertheless, the…

stat.ME2022

Renewable Learning for Multiplicative Regression with Streaming Datasets

Tianzhen Wang, Haixiang Zhang, Liuquan Sun

When large amounts of data continuously arrive in streams, online updating is an effective way to reduce storage and computational burden. The key idea of online updating is that t…

stat.ME2022★ 1 cited

Approximating Partial Likelihood Estimators via Optimal Subsampling

Haixiang Zhang, Lulu Zuo, HaiYing Wang +1

With the growing availability of large-scale biomedical data, it is often time-consuming or infeasible to directly perform traditional statistical analysis with relatively limited…