Publications

Technical Reports

• Randomization Inference with Sample Attrition.
  Xinran Li, Peizan Sheng, and Zeyang Yu. [arXiv]

• Randomization Tests for Monotone Spillover Effects.
  Shunzhuang Huang, Xinran Li, and Panos Toulis. [arXiv]

• Enhanced inference for distributions and quantiles of individual treatment effects in various experiments.
  Zhe Chen and Xinran Li. [arXiv]

• Sensitivity Analysis for the Test-Negative Design.
  Soumyabrata Kundu, Peng Ding, Xinran Li, and Jingshu Wang. [arXiv][R package]

Journal Papers

• Sensitivity Analysis for Observational Studies with Flexible Matched Designs.
  Xinran Li. Biometrika, to appear. [arXiv]

• Sensitivity Analysis for Quantiles of Hidden Biases in Matched Observational Studies.
  Dongxiao Wu and Xinran Li. Journal of the American Statistical Association, to appear. [arXiv][journal][R package]

• Asymptotic Theory of the Best-Choice Rerandomization using the Mahalanobis Distance.
  Yuhao Wang and Xinran Li. Journal of Econometrics, 251:106049, 2025. [arXiv][journal]

• Randomization-based Z-estimation for evaluating average and individual treatment effects
  Tianyi Qu, Jiangchuan Du, and Xinran Li. Biometrika, 112, 2025. [arXiv][journal]

• Some theoretical foundations for the design and analysis of randomized experiments.
  Lei Shi and Xinran Li. Journal of Causal Inference, 12, 2024. [arXiv][journal]

• The role of randomization inference in unraveling individual treatment effects in early phase vaccine trials.
  Zhe Chen, Xinran Li, and Bo Zhang. Statistical Communications in Infectious Diseases, 16, 2024. [arXiv][journal]

• Treatment Effect Quantiles in Stratified Randomized Experiments and Matched Observational Studies.
  Yongchang Su and Xinran Li. Biometrika, 111:235–254, 2024. [journal][arXiv][R package]

• Power and Sample Size Calculations for Rerandomized Experiments.
  Zach Branson, Xinran Li, and Peng Ding. Biometrika, 111:355–363, 2024. [journal][arXiv]

• Randomization Inference beyond the Sharp Null: Bounded Null Hypotheses and Quantiles of Individual Treatment Effects.
  Devin Caughey, Allan Dafoe, Xinran Li, and Luke Miratrix. Journal of the Royal Statistical Society: Series B, 85:1471–1491, 2023. [journal][arXiv][R package][video]

• Randomization-based Test for Censored Outcomes: A New Look at the Logrank Test.
  Xinran Li and Dylan S. Small. Statistical Science, 38:92–107, 2023. [journal][arXiv]

• Rejective Sampling, Rerandomization and Regression Adjustment in Survey Experiments.
  Zihao Yang, Tianyi Qu, and Xinran Li. Journal of the American Statistical Association, 118:1207–1221, 2023. [journal][arXiv][R package]

• Kernel-based Partial Permutation Test for Detecting Heterogeneous Functional Relationship.
  Xinran Li, Bo Jiang, and Jun S. Liu. Journal of the American Statistical Association, 118:1429-1447, 2023. [journal][arXiv]

• Rerandomization with Diminishing Covariate Imbalance and Diverging Number of Covariates.
  Yuhao Wang and Xinran Li. Annals of Statistics, 50:3439–3465, 2022. [journal][arXiv]

• Bayesian Analysis of Rank Data with Covariates and Heterogeneous Rankers.
  Xinran Li, Dingdong Yi, and Jun S. Liu. Statistical Science, 37:1–23, 2022. [journal][arXiv][R package]

• On the Optimality of Sliced Inverse Regression in High Dimensions.
  Qian Lin, Xinran Li, Dongming Huang, and Jun S. Liu. Annals of Statistics, 49:1–20, 2021. [journal][arXiv]

• A Multi-Resolution Theory for Approximating Infinite-p-Zero-n: Transitional Inference, Individualized Predictions, and a World Without Bias-Variance Trade-off.
  Xinran Li and Xiao-Li Meng. Journal of the American Statistical Association, 116:353–367, 2021. [journal][arXiv]

• Rerandomization and Regression Adjustment.
  Xinran Li and Peng Ding. Journal of the Royal Statistical Society: Series B, 82:241–268, 2020. [journal][arXiv]

• Rerandomization in $2^K$ Factorial Experiments.
  Xinran Li, Peng Ding, and Donald B. Rubin. Annals of Statistics, 48:43–63, 2020. [journal][arXiv][slides]

• Randomization Inference for Peer Effects.
  Xinran Li, Peng Ding, Qian Lin, Dawei Yang, and Jun S. Liu. Journal of the American Statistical Association, 114:1651–1664, 2019. [journal][arXiv]

• Asymptotic Theory of Rerandomization in Treatment-Control Experiments.
  Xinran Li, Peng Ding, and Donald B. Rubin. Proceedings of the National Academy of Sciences, 115:9157–9162, 2018. [journal][arXiv]

• General Forms of Finite Population Central Limit Theorems with Applications to Causal Inference.
  Xinran Li and Peng Ding. Journal of the American Statistical Association, 112:1759–1769, 2017. [journal][arXiv]

• Bridging Finite and Super Population Causal Inference.
  Peng Ding, Xinran Li, and Luke W. Miratrix. Journal of Causal Inference, 5, 2017. [journal][arXiv]

• Exact Confidence Intervals for the Average Causal Effect on a Binary Outcome.
  Xinran Li and Peng Ding. Statistics in Medicine, 35:957–960, 2016. [journal][arXiv]