National Health and Nutrition Examination Survey, 2015-2018: Sample Design and Estimation Procedures.

Q1 Mathematics
Te-Ching Chen, Jason Clark, Minsun K Riddles, Leyla K Mohadjer, Tala H I Fakhouri
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引用次数: 0

Abstract

Background The purpose of the National Health and Nutrition Examination Survey (NHANES) is to produce national estimates representative of the total noninstitutionalized civilian U.S. population. The sample for NHANES is selected using a complex, four-stage sample design. NHANES sample weights are used by analysts to produce estimates of the health-related statistics that would have been obtained if the entire sampling frame (i.e., the noninstitutionalized civilian U.S. population) had been surveyed. Sampling errors should be calculated for all survey estimates to aid in determining their statistical reliability. For complex sample surveys, exact mathematical formulas for variance estimates that fully incorporate the sample design are usually not available. Variance approximation procedures are required to provide reasonable, approximately unbiased, and design-consistent estimates of variance. Objective This report describes the NHANES 2015-2018 sample design and the methods used to create sample weights and variance units for the public-use data files, including sample weights for selected subsamples, such as the fasting subsample. The impacts of sample design changes on estimation for NHANES 2015-2018 are described. Approaches that data users can use to modify sample weights when combining survey cycles or when combining subsamples are also included.

2015-2018年全国健康与营养检查调查:样本设计与估计程序
背景:全国健康与营养调查(NHANES)的目的是产生具有代表性的美国非收容平民总人口的全国估计。NHANES的样本是使用复杂的四阶段样本设计来选择的。分析人员使用NHANES样本权重来估计如果对整个抽样框架(即非收容的美国平民人口)进行调查,将获得的与健康有关的统计数据。应计算所有调查估计的抽样误差,以帮助确定其统计可靠性。对于复杂的抽样调查,通常没有精确的数学公式来估计完全包含抽样设计的方差。方差近似程序需要提供合理的,近似无偏的,和设计一致的方差估计。本报告描述了NHANES 2015-2018样本设计以及用于创建公共使用数据文件的样本权重和方差单位的方法,包括选定子样本的样本权重,如禁食子样本。描述了样品设计变化对NHANES 2015-2018估计的影响。数据用户在组合调查周期或组合子样本时可以用来修改样本权重的方法也包括在内。
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来源期刊
CiteScore
13.20
自引率
0.00%
发文量
0
期刊介绍: Studies of new statistical methodology including experimental tests of new survey methods, studies of vital statistics collection methods, new analytical techniques, objective evaluations of reliability of collected data, and contributions to statistical theory. Studies also include comparison of U.S. methodology with those of other countries.
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