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Adjusted logistic propensity weighting methods for population inference using nonprobability volunteer-based epidemiologic cohorts
Statistics in Medicine ( IF 1.8 ) Pub Date : 2021-07-05 , DOI: 10.1002/sim.9122
Lingxiao Wang 1 , Richard Valliant 1, 2 , Yan Li 1
Affiliation  

Many epidemiologic studies forgo probability sampling and turn to nonprobability volunteer-based samples because of cost, response burden, and invasiveness of biological samples. However, finite population (FP) inference is difficult to make from the nonprobability sample due to the lack of population representativeness. Aiming for making inferences at the population level using nonprobability samples, various inverse propensity score weighting methods have been studied with the propensity defined by the participation rate of population units in the nonprobability sample. In this article, we propose an adjusted logistic propensity weighting (ALP) method to estimate the participation rates for nonprobability sample units. The proposed ALP method is easy to implement by ready-to-use software while producing approximately unbiased estimators for population quantities regardless of the nonprobability sample rate. The efficiency of the ALP estimator can be further improved by scaling the survey sample weights in propensity estimation. Taylor linearization variance estimators are proposed for ALP estimators of FP means that account for all sources of variability. The proposed ALP methods are evaluated numerically via simulation studies and empirically using the naïve unweighted National Health and Nutrition Examination Survey III sample, while taking the 1997 National Health Interview Survey as the reference, to estimate the 15-year mortality rates.

中文翻译:

使用基于非概率志愿者的流行病学队列进行人口推断的调整后逻辑倾向加权方法

由于生物样本的成本、反应负担和侵入性,许多流行病学研究放弃了概率抽样,转而使用非概率的志愿者样本。然而,由于缺乏总体代表性,很难从非概率样本中进行有限总体 (FP) 推断。为了使用非概率样本在总体水平上进行推断,已经研究了各种逆倾向得分加权方法,其倾向由非概率样本中的总体单元参与率定义。在本文中,我们提出了一种调整后的逻辑倾向加权 (ALP) 方法来估计非概率样本单元的参与率。所提出的 ALP 方法很容易通过现成的软件实现,同时无论非概率采样率如何,都可以为总体数量生成近似无偏的估计量。通过在倾向估计中缩放调查样本权重,可以进一步提高 ALP 估计器的效率。为 FP 均值的 ALP 估计量提出了泰勒线性化方差估计量,以说明所有可变性来源。提议的 ALP 方法通过模拟研究进行数值评估,并使用朴素的未加权全国健康和营养检查调查 III 样本进行经验评估,同时以 1997 年全国健康访谈调查为参考,估计 15 年死亡率。通过在倾向估计中缩放调查样本权重,可以进一步提高 ALP 估计器的效率。为 FP 均值的 ALP 估计量提出了泰勒线性化方差估计量,以说明所有可变性来源。提议的 ALP 方法通过模拟研究进行数值评估,并使用朴素的未加权全国健康和营养检查调查 III 样本进行经验评估,同时以 1997 年全国健康访谈调查为参考,估计 15 年死亡率。通过在倾向估计中缩放调查样本权重,可以进一步提高 ALP 估计器的效率。为 FP 均值的 ALP 估计量提出了泰勒线性化方差估计量,以说明所有可变性来源。提议的 ALP 方法通过模拟研究进行数值评估,并使用朴素的未加权全国健康和营养检查调查 III 样本进行经验评估,同时以 1997 年全国健康访谈调查为参考,估计 15 年死亡率。
更新日期:2021-07-05
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