使用基于秩的方法,为具有海量生存数据的半参数加速失效时间模型优化子采样。

IF 1.8 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Statistics in Medicine Pub Date : 2024-10-30 Epub Date: 2024-08-20 DOI:10.1002/sim.10200
Zehan Yang, HaiYing Wang, Jun Yan
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引用次数: 0

摘要

子采样是分析大量生存数据的一种实用策略,在不同的研究领域都会逐渐遇到。虽然最优子抽样方法已被应用于 Cox 模型和参数加速失效时间(AFT)模型的推断,但其在基于秩估计的半参数 AFT 模型中的应用却受到了有限的关注。所面临的挑战来自回归系数的非光滑估计函数,以及在通常形式的估计函数中,删减观测值的贡献似乎为零。为了应对这些挑战,我们通过一个定义明确的随机过程来表达估计函数,从而为事件和删减观测值开发出最优的子采样概率。同时,我们对不平滑的估计函数采用了诱导平滑程序。由于最佳子采样概率取决于未知回归系数,我们采用了两步程序来获得可行的估计方法。该方法的另一个优点是,当子样本规模接近全样本规模时,它能解决方差估计不足的问题。我们通过模拟研究验证了估计方法的性能,并将这些方法用于分析监测、流行病学和最终结果项目中淋巴瘤患者的生存时间。
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Optimal subsampling for semi-parametric accelerated failure time models with massive survival data using a rank-based approach.

Subsampling is a practical strategy for analyzing vast survival data, which are progressively encountered across diverse research domains. While the optimal subsampling method has been applied to inferences for Cox models and parametric accelerated failure time (AFT) models, its application to semi-parametric AFT models with rank-based estimation have received limited attention. The challenges arise from the non-smooth estimating function for regression coefficients and the seemingly zero contribution from censored observations in estimating functions in the commonly seen form. To address these challenges, we develop optimal subsampling probabilities for both event and censored observations by expressing the estimating functions through a well-defined stochastic process. Meanwhile, we apply an induced smoothing procedure to the non-smooth estimating functions. As the optimal subsampling probabilities depend on the unknown regression coefficients, we employ a two-step procedure to obtain a feasible estimation method. An additional benefit of the method is its ability to resolve the issue of underestimation of the variance when the subsample size approaches the full sample size. We validate the performance of our estimators through a simulation study and apply the methods to analyze the survival time of lymphoma patients in the surveillance, epidemiology, and end results program.

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来源期刊
Statistics in Medicine
Statistics in Medicine 医学-公共卫生、环境卫生与职业卫生
CiteScore
3.40
自引率
10.00%
发文量
334
审稿时长
2-4 weeks
期刊介绍: The journal aims to influence practice in medicine and its associated sciences through the publication of papers on statistical and other quantitative methods. Papers will explain new methods and demonstrate their application, preferably through a substantive, real, motivating example or a comprehensive evaluation based on an illustrative example. Alternatively, papers will report on case-studies where creative use or technical generalizations of established methodology is directed towards a substantive application. Reviews of, and tutorials on, general topics relevant to the application of statistics to medicine will also be published. The main criteria for publication are appropriateness of the statistical methods to a particular medical problem and clarity of exposition. Papers with primarily mathematical content will be excluded. The journal aims to enhance communication between statisticians, clinicians and medical researchers.
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