Improving estimation efficiency for two-phase, outcome-dependent sampling studies

IF 1 4区 数学 Q3 STATISTICS & PROBABILITY Electronic Journal of Statistics Pub Date : 2022-12-19 DOI:10.1214/23-ejs2124
Menglu Che, Peisong Han, J. Lawless
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Abstract

Two-phase outcome dependent sampling (ODS) is widely used in many fields, especially when certain covariates are expensive and/or difficult to measure. For two-phase ODS, the conditional maximum likelihood (CML) method is very attractive because it can handle zero Phase 2 selection probabilities and avoids modeling the covariate distribution. However, most existing CML-based methods use only the Phase 2 sample and thus may be less efficient than other methods. We propose a general empirical likelihood method that uses CML augmented with additional information in the whole Phase 1 sample to improve estimation efficiency. The proposed method maintains the ability to handle zero selection probabilities and avoids modeling the covariate distribution, but can lead to substantial efficiency gains over CML in the inexpensive covariates, or in the influential covariate when a surrogate is available, because of an effective use of the Phase 1 data. Simulations and a real data illustration using NHANES data are presented.
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提高两阶段、结果相关抽样研究的估计效率
两阶段结果相关采样(ODS)在许多领域被广泛使用,尤其是当某些协变量昂贵和/或难以测量时。对于两相ODS,条件最大似然(CML)方法非常有吸引力,因为它可以处理零的第二阶段选择概率,并避免对协变量分布进行建模。然而,大多数现有的基于CML的方法仅使用阶段2样本,因此可能不如其他方法有效。我们提出了一种通用的经验似然方法,该方法使用在整个阶段1样本中增加额外信息的CML来提高估计效率。所提出的方法保持了处理零选择概率的能力,并避免了对协变量分布进行建模,但由于有效地使用了第1阶段数据,在廉价的协变量中,或在有替代项的情况下,在有影响的协变量上,可以显著提高CML的效率。给出了使用NHANES数据的模拟和实际数据说明。
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来源期刊
Electronic Journal of Statistics
Electronic Journal of Statistics STATISTICS & PROBABILITY-
CiteScore
1.80
自引率
9.10%
发文量
100
审稿时长
3 months
期刊介绍: The Electronic Journal of Statistics (EJS) publishes research articles and short notes on theoretical, computational and applied statistics. The journal is open access. Articles are refereed and are held to the same standard as articles in other IMS journals. Articles become publicly available shortly after they are accepted.
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