关于复杂调查数据的多稳健预测均值匹配估算的说明。

IF 1.2 4区 数学 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS Survey Methodology Pub Date : 2021-06-01 Epub Date: 2021-06-24
Sixia Chen, David Haziza, Alexander Stubblefield
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引用次数: 0

摘要

预测均值匹配是一种常用的估算程序,用于解决调查中的项目无响应问题。传统方法依赖于指定单一结果回归模型。在本说明中,我们提出了一种新颖的预测均值匹配程序,允许用户指定多个结果回归模型。由此产生的估计器具有多重稳健性,即只要指定的结果回归模型之一正确,估计器就能保持一致。模拟研究的结果表明,所提出的方法在偏差和效率方面表现良好。
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A note on multiply robust predictive mean matching imputation with complex survey data.

Predictive mean matching is a commonly used imputation procedure for addressing the problem of item nonrespone in surveys. The customary approach relies upon the specification of a single outcome regression model. In this note, we propose a novel predictive mean matching procedure that allows the user to specify multiple outcome regression models. The resulting estimator is multiply robust in the sense that it remains consistent if one of the specified outcome regression models is correctly specified. The results from a simulation study suggest that the proposed method performs well in terms of bias and efficiency.

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来源期刊
Survey Methodology
Survey Methodology 数学-统计学与概率论
CiteScore
0.80
自引率
22.20%
发文量
0
审稿时长
>12 weeks
期刊介绍: The journal publishes articles dealing with various aspects of statistical development relevant to a statistical agency, such as design issues in the context of practical constraints, use of different data sources and collection techniques, total survey error, survey evaluation, research in survey methodology, time series analysis, seasonal adjustment, demographic studies, data integration, estimation and data analysis methods, and general survey systems development. The emphasis is placed on the development and evaluation of specific methodologies as applied to data collection or the data themselves.
期刊最新文献
The anchoring method: Estimation of interviewer effects in the absence of interpenetrated sample assignment. A note on multiply robust predictive mean matching imputation with complex survey data. Optimum allocation for a dual-frame telephone survey. Combining information from multiple complex surveys. A nonparametric method to generate synthetic populations to adjust for complex sampling design features.
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