Zobrazeno 1 - 10
of 109 888
pro vyhledávání: '"Cox Model"'
Autor:
Zhang, Yunwei1,2,3 (AUTHOR) yunwei.zhang@murdoch.edu.au, Muller, Samuel2,3 (AUTHOR)
Publikováno v:
Briefings in Bioinformatics. Nov2024, Vol. 25 Issue 6, p1-9. 9p.
Autor:
Chatton, Arthur, Pilote, Émilie, Feugo, Kevin Assob, Cardinal, Héloïse, Platt, Robert W., Schnitzer, Mireille E
Objective: This study sought to compare the drop in predictive performance over time according to the modeling approach (regression versus machine learning) used to build a kidney transplant failure prediction model with a time-to-event outcome. Stud
Externí odkaz:
http://arxiv.org/abs/2412.10252
Autor:
Kwok, Ngok Sang, Wong, Kin Yau
Regression analysis with missing data is a long-standing and challenging problem, particularly when there are many missing variables with arbitrary missing patterns. Likelihood-based methods, although theoretically appealing, are often computationall
Externí odkaz:
http://arxiv.org/abs/2410.11482
We develop a set of variable selection methods for the Cox model under interval censoring, in the ultra-high dimensional setting where the dimensionality can grow exponentially with the sample size. The methods select covariates via a penalized nonpa
Externí odkaz:
http://arxiv.org/abs/2405.01275
Autor:
Etievant, Lola, Gail, Mitchell H.
The case-cohort design allows analysis of multiple endpoints and only requires covariates to be measured for cases and non-cases in a random subcohort from the cohort. Stratification of subcohort sampling and weight calibration increase efficiency of
Externí odkaz:
http://arxiv.org/abs/2402.08744
Autor:
Jiang, Meng1 jmhust@zju.edu.cn, Wu, Xiao-peng2, Li, Chang-li3, Lin, Xing-chen1, Yang, Xiao-feng1 zjcswk@zju.edu.cn
Publikováno v:
Intensive Care Research. Sep2024, Vol. 4 Issue 3, p162-170. 9p.
In this paper we address the challenges posed by non-proportional hazards and informative censoring, offering a path toward more meaningful causal inference conclusions. We start from the marginal structural Cox model, which has been widely used for
Externí odkaz:
http://arxiv.org/abs/2311.07752
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 s
Externí odkaz:
http://arxiv.org/abs/2310.08208
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