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

• URL: http://arxiv.org/abs/2310.02278v2
• Date: Wed, 15 May 2024 19:38:45 GMT
• Title: A Stable and Efficient Covariate-Balancing Estimator for Causal Survival Effects
• Authors: Khiem Pham, David A. Hirshberg, Phuong-Mai Huynh-Pham, Michele Santacatterina, Ser-Nam Lim, Ramin Zabih,
• Abstract summary: We address the problem of estimating survival causal effects in data with conditionally-independent censoring. This addresses 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.
• Score: 33.62020029799266
• License: http://creativecommons.org/licenses/by/4.0/
• 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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