Handling Missing Values in Surveys With Complex Study Design: A Simulation Study

IF 1.6 4区数学 Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS

Journal of Survey Statistics and Methodology Pub Date : 2023-02-20 DOI:10.1093/jssam/smac039

N. Kalpourtzi, James R. Carpenter, G. Touloumi

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引用次数: 2

Abstract

The inverse probability weighting (IPW) method is commonly used to deal with missing-at-random outcome (response) data collected by surveys with complex sampling designs. However, IPW methods generally assume that fully observed predictor variables are available for all sampled units, and it is unclear how to appropriately implement these methods when one or more independent variables are subject to missing values. Multiple imputation (MI) methods are well suited for a variety of missingness patterns but are not as easily adapted to complex sampling designs. In this case study, we consider the National Survey of Morbidity and Risk Factors (EMENO), a multistage probability sample survey. To understand the strengths and limitations of using either missing data treatment method for the EMENO, we present an extensive simulation study modeled on the EMENO health survey, with the target analysis being the estimation of population prevalence of hypertension as well as the association between hypertension and income. Both variables are subject to missingness. We test a variety of IPW and MI methods in simulation and on empirical data from the survey, assessing robustness by varying missingness mechanisms, proportions of missingness, and strengths of fitted response propensity models.

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用复杂的研究设计处理调查中的缺失值：一项模拟研究

反概率加权（IPW）方法通常用于处理通过复杂抽样设计的调查收集的随机结果（响应）数据的缺失。然而，IPW方法通常假设所有采样单元都可以获得完全观察到的预测变量，并且当一个或多个自变量存在缺失值时，尚不清楚如何适当地实现这些方法。多重插补（MI）方法非常适合各种缺失模式，但不太容易适应复杂的抽样设计。在本案例研究中，我们考虑了全国发病率和风险因素调查（EMENO），这是一项多阶段概率抽样调查。为了了解EMENO使用缺失数据处理方法的优势和局限性，我们在EMENO健康调查的基础上进行了一项广泛的模拟研究，目标分析是估计高血压的人群患病率以及高血压与收入之间的关系。这两个变量都可能缺失。我们在模拟和调查的经验数据上测试了各种IPW和MI方法，通过不同的缺失机制、缺失比例和拟合的反应倾向模型的强度来评估稳健性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Survey Statistics and Methodology Multiple-

CiteScore

4.30

自引率

9.50%

发文量

期刊介绍： The Journal of Survey Statistics and Methodology, sponsored by AAPOR and the American Statistical Association, began publishing in 2013. Its objective is to publish cutting edge scholarly articles on statistical and methodological issues for sample surveys, censuses, administrative record systems, and other related data. It aims to be the flagship journal for research on survey statistics and methodology. Topics of interest include survey sample design, statistical inference, nonresponse, measurement error, the effects of modes of data collection, paradata and responsive survey design, combining data from multiple sources, record linkage, disclosure limitation, and other issues in survey statistics and methodology. The journal publishes both theoretical and applied papers, provided the theory is motivated by an important applied problem and the applied papers report on research that contributes generalizable knowledge to the field. Review papers are also welcomed. Papers on a broad range of surveys are encouraged, including (but not limited to) surveys concerning business, economics, marketing research, social science, environment, epidemiology, biostatistics and official statistics. The journal has three sections. The Survey Statistics section presents papers on innovative sampling procedures, imputation, weighting, measures of uncertainty, small area inference, new methods of analysis, and other statistical issues related to surveys. The Survey Methodology section presents papers that focus on methodological research, including methodological experiments, methods of data collection and use of paradata. The Applications section contains papers involving innovative applications of methods and providing practical contributions and guidance, and/or significant new findings.