collaborators

5 papers

math.ST2026

Misspecified regressions with mixed regressors: robust inference and causal interpretation

Mengsi Gao, Peng Ding

For analytic convenience, existing statistical frameworks either assume random or fixed regressors. However, it is a little awkward that they do not cover the practical case of est…

stat.ME2026

Introducing the CP-plot Based on Covariance Representations of Weighted Average Treatment Effects

Pengfei Tian, Fan Yang, Peng Ding

Under the canonical setting of observational studies for causal inference, we derive a set of exact representations for pairwise differences among weighted average treatment effect…

stat.ME2025

Sensitivity Analysis for Unmeasured Confounding in Medical Product Development and Evaluation Using Real World Evidence

Yixin Fang, Pallavi Mishra-Kalyani, Xiang Zhang +8

The American Statistical Association Biopharmaceutical Section (ASA BIOP) scientific working group on real-world evidence (RWE) has been making continuous, extended efforts towards…

stat.ME2025

Berry-Esseen bounds for design-based causal inference with possibly diverging treatment levels and varying group sizes

Lei Shi, Peng Ding

Neyman (1923/1990) introduced the randomization model, which contains the notation of potential outcomes to define causal effects and a framework for large-sample inference based o…

stat.ME2025

Interpretable sensitivity analysis for the Baron-Kenny approach to mediation with unmeasured confounding

Mingrui Zhang, Peng Ding

Mediation analysis assesses the extent to which the exposure affects the outcome indirectly through a mediator and the extent to which it operates directly through other pathways.…