- Policy Learning with Asymmetric Counterfactual Utilities
Ben-Michael, E., Imai, K. and Jiang, Z.
Journal of the American Statistical Association, 2024 [DOI] - An Instrumental Variable Method for Point Processes: Generalized Wald Estimation Based on Deconvolution
Jiang, Z., Chen, S. and Ding, P.
Biometrika, 110, 989--1008, 2023 [DOI] - Statistical Inference and Power Analysis for Direct and Spillover Effects in Two-Stage Randomized Experiments
Jiang, Z. and Imai, K.
Biometrics, 79, 2370--2381, 2023 [DOI] - Experimental evaluation of algorithm-assisted human decision-making: application to pretrial public safety assessment (with discussion)
Imai, K., Jiang, Z., Greiner, J., Halen, R. and Shin, S.
Journal of the Royal Statistical Society: Series A (Statistics in Society), 186, 167--189, 2023 [DOI] - Principal Fairness for Human and Algorithmic Decision-Making
Imai, K., Jiang, Z.
Statistical Science, 38, 317--328, 2022 [DOI] - Multiply robust estimation of causal effects under principal ignorability
Jiang, Z., Yang, S. and Ding, P.
Journal of the Royal Statistical Society: Series B (Statistical Methodology), 84, 1423--1445, 2022 [DOI] - Identification of causal effects within principal strata using auxiliary variables
Jiang, Z. and Ding, P.
Statistical Science, 36, 493-508, 2021 [arXiv] - Causal inference with interference and noncompliance in the two-stage randomized experiments
Imai, K., Jiang, Z.* and Malani, A.
Journal of the American Statistical Association, 116, 632-644, 2021 [DOI] - Measurement errors in the binary instrumental variable model
Jiang, Z. and Ding, P.
Biometrika, 107, 238-245, 2020 [DOI] - Identification and sensitivity analysis of contagion effects with randomized placebo-controlled trials
Imai, K. and Jiang, Z.*
Journal of the Royal Statistical Society: Series A (Statistics in Society), 183, 1637-1657, 2020 [DOI] - Comment: the challenges of multiple causes
Imai, K. and Jiang, Z.
Journal of the American Statistical Association, 114, 1605-1610, 2020 [DOI] - Causal mediation analysis in the presence of a misclassified binary exposure
Jiang, Z. and VanderWeele, T. J.
Epidemiologic Methods, 2019 [DOI] - A sensitivity analysis for missing outcomes due to truncation-by-death under the matched-pairs design
Imai, K., and Jiang, Z.*
Statistics in Medicine, 37, 2907-2922, 2018 [DOI] - Using missing types to improve partial identification with application to a study of HIV prevalence in Malawi
Jiang, Z. and Ding, P.
Annals of Applied Statistics, 12, 1831-1852, 2018 [DOI] - Identification of causal effects with latent confounding and classical additive errors in treatment
Li, W., Jiang, Z., Geng, Z. and Zhou, XH.
Biometrical Journal, 60, 498-515, 2018 [DOI] - The Directions of Selection Bias
Jiang, Z. and Ding, P.
Statistics and Probability Letters, 125, 104-109, 2017 [DOI] - Robust modeling using non-elliptically contoured multivariate $t$ distributions
Jiang, Z. and Ding, P.
Journal of Statistical Planning and Inference, 177, 50-63, 2016 [DOI] - Principal causal effect identification and surrogate endpoint evaluation by multiple trials
Jiang, Z., Ding, P. and Geng, Z.
Journal of the Royal Statistical Society: Series B (Statistical Methodology), 78, 829-848, 2016 [DOI] - When is the difference method conservative for mediation? (with discussion)
Bounds or sensitivity analysis? Which to prefer for mediation? (rejoinder to discussion)
Jiang, Z. and VanderWeele, T. J.
American Journal of Epidemiology, 182, 105–117, 2015 [DOI] [DOI:rejoinder] - Qualitative evaluation of associations by the transitivity of the association signs
Jiang, Z., Ding, P. and Geng, Z.
Statistica Sinica, 25, 1065–1079, 2015 [DOI] - Causal mediation analysis in the presence of a mismeasured outcome
Jiang, Z. and VanderWeele, T. J.
Epidemiology, 26, e8-e9, 2015 [DOI] - Additive interaction in the presence of a mismeasured outcome
Jiang, Z. and VanderWeele, T. J.
American Journal of Epidemiology, 181, 81-82, 2015 [DOI] - Monotone confounding, monotone treatment selection, and monotone treatment response
Jiang, Z., Chiba, Y. and VanderWeele, T. J.
Journal of Causal Inference, 2, 1-12, 2014 [DOI]