Yunshu Zhang

College of Sciences

Works (4)

Updated: August 29th, 2023 11:25

2022 article

Multiply robust matching estimators of average and quantile treatment effects

Yang, S., & Zhang, Y. (2022, April 7). SCANDINAVIAN JOURNAL OF STATISTICS, Vol. 4.

By: S. Yang n  & Y. Zhang n

author keywords: Bahadur representation; causal effect on the treated; double robustness; quantile estimation; weighted bootstrap
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: April 18, 2022

2021 article

Practical recommendations on double score matching for estimating causal effects

Zhang, Y., Yang, S., Ye, W., Faries, D. E., Lipkovich, I., & Kadziola, Z. (2021, December 26). STATISTICS IN MEDICINE, Vol. 12.

By: Y. Zhang n, S. Yang n , W. Ye *, D. Faries *, I. Lipkovich * & Z. Kadziola*

author keywords: average treatment effect on the treated; causal inference; double robustness; prognostic score; propensity score
MeSH headings : Bias; Causality; Computer Simulation; Humans; Propensity Score
TL;DR: DSM is doubly robust in the sense that the matching estimator is consistent requiring either the propensity score model or the prognostic score model is correctly specified, and this study supports that DSM performs favorably with, if not better than, the two single score matching in terms of bias and variance. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: January 3, 2022

2020 journal article

High-Dimensional Precision Medicine From Patient-Derived Xenografts

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 116(535), 1140–1154.

By: N. Rashid *, D. Luckett*, J. Chen *, M. Lawson*, L. Wang n, Y. Zhang n, E. Laber n, Y. Liu * ...

author keywords: Biomarkers; Deep learning autoencoders; Machine learning; Outcome weighted learning; Precision medicine; Q-learning
TL;DR: This paper analyzes data from a large PDX study to identify biomarkers that are informative for developing personalized treatment recommendations in multiple cancers and implements a superlearner approach to combine a set of estimated ITRs, indicating that PDX data are a valuable resource for developing individualized treatment strategies in oncology. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: November 30, 2020

2020 journal article

Sharp bounds on the relative treatment effect for ordinal outcomes

BIOMETRICS, 76(2), 664–669.

By: J. Lu *, Y. Zhang n & P. Ding *

author keywords: causal inference; partial identification; potential outcomes
MeSH headings : Biometry; Cardia; Causality; Computer Simulation; Female; Humans; Male; Models, Statistical; Observational Studies as Topic / statistics & numerical data; Outcome Assessment, Health Care / statistics & numerical data; Randomized Controlled Trials as Topic / statistics & numerical data; Rape / prevention & control; Stomach Neoplasms / mortality; Stomach Neoplasms / therapy; Treatment Outcome
TL;DR: It is argued that the relative treatment effect can be a useful measure, especially for ordinal outcomes, and the sharp bounds on γ are derived, which are identifiable parameters based on the observed data. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: December 2, 2019

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