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Hauptverfasser: Zhang, Haixiang, Li, Yang, Wang, HaiYing
Format: Preprint
Veröffentlicht: 2023
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2310.08208
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author Zhang, Haixiang
Li, Yang
Wang, HaiYing
author_facet Zhang, Haixiang
Li, Yang
Wang, HaiYing
contents To ensure privacy protection and alleviate computational burden, we propose a fast subsmaling procedure for the Cox model with massive survival datasets from multi-centered, decentralized sources. The proposed estimator is computed based on optimal subsampling probabilities that we derived and enables transmission of subsample-based summary level statistics between different storage sites with only one round of communication. For inference, the asymptotic properties of the proposed estimator were rigorously established. An extensive simulation study demonstrated that the proposed approach is effective. The methodology was applied to analyze a large dataset from the U.S. airlines.
format Preprint
id arxiv_https___arxiv_org_abs_2310_08208
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle DsubCox: A Fast Subsampling Algorithm for Cox Model with Distributed and Massive Survival Data
Zhang, Haixiang
Li, Yang
Wang, HaiYing
Computation
To ensure privacy protection and alleviate computational burden, we propose a fast subsmaling procedure for the Cox model with massive survival datasets from multi-centered, decentralized sources. The proposed estimator is computed based on optimal subsampling probabilities that we derived and enables transmission of subsample-based summary level statistics between different storage sites with only one round of communication. For inference, the asymptotic properties of the proposed estimator were rigorously established. An extensive simulation study demonstrated that the proposed approach is effective. The methodology was applied to analyze a large dataset from the U.S. airlines.
title DsubCox: A Fast Subsampling Algorithm for Cox Model with Distributed and Massive Survival Data
topic Computation
url https://arxiv.org/abs/2310.08208