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arXiv · 2310.02278

A Stable and Efficient Covariate-Balancing Estimator for Causal Survival Effects

Khiem Pham·David A. Hirshberg·Phuong-Mai Huynh-Pham·Michele Santacatterina·Ser-Nam Lim·Ramin Zabih
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Abstract

We propose an empirically stable and asymptotically efficient covariate-balancing approach to the problem of estimating survival causal effects in data with conditionally-independent censoring. This addresses a challenge often encountered in state-of-the-art nonparametric methods: the use of inverses of small estimated probabilities and the resulting amplification of estimation error. We validate our theoretical results in experiments on synthetic and semi-synthetic data.

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Khiem Pham, David A. Hirshberg, Phuong-Mai Huynh-Pham, Michele Santacatterina, Ser-Nam Lim, Ramin Zabih. 2023-10-01. A Stable and Efficient Covariate-Balancing Estimator for Causal Survival Effects. https://arxiv.org/abs/2310.02278

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