论文标题
使用基于志愿者的流行病学人群的调整后的logistic倾向加权方法用于人口推断
Adjusted Logistic Propensity Weighting Methods for Population Inference using Nonprobability Volunteer-Based Epidemiologic Cohorts
论文作者
论文摘要
许多流行病学研究放弃了概率取样，并因生物样品的成本，响应负担和侵入性而转向基于志愿者的非企业样本。但是，由于缺乏人口代表性，很难从非企业样本中得出有限的人口推断。为了使用非概率样本对人口水平进行推断，已经研究了各种反向倾向得分加权（IPSW）方法，并通过非概率样本中人口单位的参与率定义了倾向。在本文中，我们提出了一种调整后的逻辑倾向加权（ALP）方法，以估算非概况样本单位的参与率。与现有的IPSW方法相比，提出的ALP方法可以通过即用软件易于实现，同时可为人口数量生成大约无偏见的估计量，而不管非概率的样本率如何。通过根据倾向估计来扩展调查样品权重，可以进一步提高ALP估计器的效率。提出了针对有限种群的ALP估计量提出的泰勒线性化方差估计器，这意味着解释了所有可变性的来源。通过模拟研究对所提出的ALP方法进行数值评估，并在以1997年的1997年国家健康访谈调查为参考的同时，使用幼稚的未加权的国家健康和营养检查调查III样本进行经验评估。
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 inference is difficult to make from the nonprobability samples due to the lack of population representativeness. Aiming for making inferences at the population level using nonprobability samples, various inverse propensity score weighting (IPSW) methods have been studied with the propensity defined by the participation rate of population units in the nonprobability sample. In this paper, we propose an adjusted logistic propensity weighting (ALP) method to estimate the participation rates for nonprobability sample units. Compared to existing IPSW methods, 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 finite population 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.
