Xiao‐Hua Zhou

发表

Methods for clustered encouragement design studies with noncompliance and missing data.

L. Taylor, Xiao‐Hua Zhou, 2011, Biostatistics.

Estimating causal effects of treatment in RCTs with provider and subject noncompliance

Elisa Sheng, Xiao‐Hua Zhou, Wei Li, 2018, Statistics in medicine.

Clustered encouragement designs with individual noncompliance: bayesian inference with randomization, and application to advance directive forms.

Xiao-Hua Zhou, Constantine E Frangakis, Donald B Rubin, 2002, Biostatistics.

A smoothed Q‐learning algorithm for estimating optimal dynamic treatment regimes

Yanqin Fan, Liangjun Su, Xiao‐Hua Zhou, 2018, Scandinavian Journal of Statistics.

Using secondary outcome to sharpen bounds for treatment harm rate in characterizing heterogeneity

Xiao‐Hua Zhou, Yunjian Yin, Zhenghao Cai, 2018, Biometrical journal. Biometrische Zeitschrift.

Robust Estimation of Propensity Score Weights via Subclassification

T. Richardson, Xiao‐Hua Zhou, Linbo Wang, 2016, 1602.06366.

On rank estimators in increasing dimensions

Fang Han, Yanqin Fan, Xiao‐Hua Zhou, 2019, Journal of Econometrics.

Hypothesis testing for differentially correlated features.

D. Witten, Elisa Sheng, Xiao‐Hua Zhou, 2016, Biostatistics.

BATE curve in assessment of clinical utility of predictive biomarkers

Xiao‐Hua Zhou, Yunbei Ma, 2012 .

Relaxing Latent Ignorability in the ITT Analysis of Randomized Studies with Missing Data and Noncompliance

L. Taylor, Xiao‐Hua Zhou, 2009 .

Identification of causal effects with latent confounding and classical additive errors in treatment

Z. Geng, Zhichao Jiang, Xiao‐Hua Zhou, 2018, Biometrical journal. Biometrische Zeitschrift.

Causal mediation analysis on failure time outcome without sequential ignorability

C. Zheng, Xiao‐Hua Zhou, 2017, Lifetime data analysis.

Doubly Robust Collaborative Targeted Learning for Recommendation on Data Missing Not at Random

Peng Wu, Xiao‐Hua Zhou, Haoxuan Li, 2022, ArXiv.

Identifiability and estimation of causal mediation effects with missing data

Xiao‐Hua Zhou, Wei Li, 2017, Statistics in medicine.

On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges

Quanyu Dai, Jie Sun, Peng Wu, 2022, IJCAI.

Estimating $c$-level partial correlation graphs with application to brain imaging.

Yumou Qiu, Xiao‐Hua Zhou, 2018, Biostatistics.

Hepatitis C Cure Is Associated with Decreased Healthcare Costs in Cirrhotics in Retrospective Veterans Affairs Cohort

L. Beste, Xiao‐Hua Zhou, M. Chapko, 2018, Digestive Diseases and Sciences.

COVARIATE-SPECIFIC AND COVARIATE-ADJUSTED PREDICTIVE VALUES OF PROGNOSTIC BIOMARKERS WITH SURVIVAL OUTCOME

Kwun Chuen Gary Chan, Xiao‐Hua Zhou, Yunbei Ma, 2015 .

Identification and estimation of causal effects with outcomes truncated by death

Thomas S. Richardson, Xiao-Hua Zhou, Linbo Wang, 2016, Biometrika.

Model Assessment for Models with Missing Data

Xiaolei Zhou, Xiao‐Hua Zhou, 2015 .

Extending Hui‐Walter framework to correlated outcomes with application to diagnosis tests of an eye disease among premature infants

G. Ying, G. Quinn, Xiao‐Hua Zhou, 2021, Statistics in medicine.

Making causal inferences about treatment effect sizes from observational datasets

Richard M. Golden, Steven S. Henley, T. Michael Kashner, 2020, Biostatistics & Epidemiology.

Inference of heterogeneous treatment effects using observational data with high‐dimensional covariates

Yumou Qiu, Xiao‐Hua Zhou, Jing Tao, 2021, Journal of the Royal Statistical Society: Series B (Statistical Methodology).

Identification and Estimation of the Heterogeneous Survivor Average Causal Effect in Observational Studies

Xiao-Hua Zhou, Yuhao Deng, Yuhang Guo, 2021 .

Identification of the Heterogeneous Survivor Average Causal Effect in Observational Studies

Yuhao Deng, Xiao‐Hua Zhou, Ying-Chao Chang, 2021 .

Causal mediation analysis on failure time outcome without sequential ignorability

Xiao‐Hua Zhou, Cheng Zheng, 2016, Lifetime Data Analysis.

Model-Assisted Inference for Covariate-Specific Treatment Effects with High-dimensional Data

Zhiqiang Tan, Xiao-Hua Zhou, Peng Wu, 2021, Statistica Sinica.

Rejoinder to discussions on clustered encouragement designs with individual noncompliance: Bayesian inference with randomization, and application to advance directive forms

Donald B. Rubin, Xiao-Hua Zhou, Constantine Frangakis, 2002 .

Identifiability and Estimation of Causal Effects in Randomized Trials with Noncompliance and Completely Nonignorable Missing Data

Zhi Geng, Xiao-Hua Zhou, Z. Geng, 2009, Biometrics.

Challenges and strategies in analysis of missing data

Xiao-Hua Zhou, Xiao‐Hua Zhou, 2020 .

Causal Analysis Framework for Recommendation pdf

Quanyu Dai, Rui Zhang, Peng Wu, 2022, ArXiv.

Weighted quantile regression for analyzing health care cost data with missing covariates

Lan Wang, Xiao-Hua Zhou, Ben Sherwood, 2013, Statistics in medicine.

Identification of the optimal treatment regimen in the presence of missing covariates

Xiao-Hua Zhou, Ying Huang, Xiao‐Hua Zhou, 2019, Statistics in medicine.

A tutorial in assessing disclosure risk in microdata

Xiao-Hua Zhou, L. Taylor, Xiao‐Hua Zhou, 2018, Statistics in medicine.

Tree-based ensemble methods for individualized treatment rules

Xiao‐Hua Zhou, Ying Huang, Kehao Zhu, 2018, Biostatistics & epidemiology.

Causal analysis in multi-arm trials with truncation by death

Thomas S. Richardson, Xiao-Hua Zhou, Linbo Wang, 2015 .

Identifiability and Estimation of Causal Effects by Principal Stratification With Outcomes Truncated by Death

Zhi Geng, Xiao-Hua Zhou, Peng Ding, 2011 .

Causal mediation analysis with sure outcomes of random events model

Z. Geng, Xiao‐Hua Zhou, Wei Li, 2021, Statistics in medicine.

On estimating causal controlled direct and mediator effects for count outcomes without assuming sequential ignorability

David C. Atkins, C. Zheng, Xiao‐Hua Zhou, 2016, 1601.06743.

Causal Models for Mediation Analysis: An Introduction to Structural Mean Models

David C. Atkins, C. Zheng, Xiao‐Hua Zhou, 2015, Multivariate behavioral research.

Causal analysis of ordinal treatments and binary outcomes under truncation by death

Thomas S Richardson, Xiao-Hua Zhou, Linbo Wang, 2015, Journal of the Royal Statistical Society. Series B, Statistical methodology.

Robust quasi-oracle semiparametric estimation of average causal effects

Xingwei Tong, Jiajuan Liang, Xiao‐Hua Zhou, 2022, Biostatistics & Epidemiology.

Assessing the effect of an influenza vaccine in an encouragement design.

D. Rubin, G. Imbens, K. Hirano, 2000, Biostatistics.

ITT analysis of randomized encouragement design studies with missing data

Xiao-Hua Zhou, Sierra M Li, Xiao‐Hua Zhou, 2006, Statistics in medicine.

Treatment selection in a randomized clinical trial via covariate-specific treatment effect curves

Xiao-Hua Zhou, Yunbei Ma, Xiao‐Hua Zhou, 2017, Statistical methods in medical research.

Hypothesis testing for differentially correlated features.

D. Witten, Elisa Sheng, Xiao‐Hua Zhou, 2016, Biostatistics.

A Semi-Synthetic Dataset Generation Framework for Causal Inference in Recommender Systems

Quanyu Dai, Peng Wu, Yuhao Deng, 2022, ArXiv.

Statistica Sinica Preprint No: SS-2023-0006

Wenjie Hu, Xiao‐Hua Zhou, Peng Wu, 2023 .

Double robust estimator of average causal treatment effect for censored medical cost data

L. Beste, Xiao‐Hua Zhou, Xuan Wang, 2016, Statistics in medicine.

A powerful test for the maximum treatment effect in thorough QT/QTc studies

Yuhao Deng, Xiao‐Hua Zhou, Rui Wang, 2021, Statistics in medicine.

Inference on Multi-level Partial Correlations Based on Multi-subject Time Series Data

Yumou Qiu, Xiao-Hua Zhou, Yumou Qiu, 2021, Journal of the American Statistical Association.

Identification and Estimation of Heterogeneous Survivor Average Causal Effect in Observational Studies

Yuhao Deng, Xiao‐Hua Zhou, Ying-Chao Chang, 2022 .