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Attributable fraction estimation from complex sample survey data

机译：来自复杂样本调查数据的归因分数估计

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摘要

Purpose: A review of methods for the estimation of attributable fraction (AF) statistics from case-control, cross-sectional, or cohort data collected under a complex sample design. Provide guidance on practical methods of complex sample AF estimation and inference using contemporary software tools. Methods: Statistical literature on AF estimation from complex samples for the period 1980 to 2014 is reviewed. A general approach based on weighted sum estimators of the AF and application of Jackknife repeated replication and Bootstrap resampling methods for estimating the variance of AF estimates is outlined and applied to an example analysis of risk factors for alcohol dependency. Results: The literature lays the theoretical foundation to address the problem of AF estimation and inference from complex samples. To date, major statistical software packages do not provide a complete program but the approach is easily implemented using the modeling software and macro/function language capabilities available in major statistical analysis packages. In an example application, weighted sum estimation and inference for the population AF showed stable and consistent results under both Jackknife repeated replication and Bootstrap methods of variance estimation. Conclusions: Future work on AF estimation for complex samples should focus on simulation studies and empirical testing to investigate the properties of the resampling variance estimation methods across a range of complex study design features and populations.
机译：目的：综述从复杂样本设计下收集的病例对照，横断面或队列数据估算归因分数（AF）统计的方法。使用现代软件工具提供有关复杂样本AF估计和推断的实用方法的指南。方法：回顾了1980年至2014年期间从复杂样本进行房颤估计的统计文献。概述了一种基于AF加权和估计器以及应用Jackknife重复复制和Bootstrap重采样方法估计AF估计值方差的通用方法，并将其应用于对酒精依赖风险因素的示例分析。结果：文献为解决AF估计和从复杂样本推断的问题奠定了理论基础。迄今为止，主要统计软件包尚未提供完整的程序，但使用主要统计分析软件包中提供的建模软件和宏/功能语言功能可轻松实现该方法。在一个示例应用程序中，在Jackknife重复复制和Bootstrap方差估计方法下，总体AF的加权总和估计和推断显示出稳定一致的结果。结论：复杂样本的AF估计的未来工作应集中在模拟研究和经验测试上，以研究在一系列复杂研究设计特征和总体范围内重采样方差估计方法的特性。

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