Estimation of the Distribution of Hourly Pay from Household Survey Data: The Use of Missing Data Methods to Handle Measurement Error

IF 1.2 4区数学 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS

Survey Methodology Pub Date : 2003-05-22 DOI:10.1920/WP.CEM.2003.1203

G. Beissel-Durrant, C. Skinner

引用次数: 2

Abstract

Measurement errors in survey data on hourly pay may lead to serious upward bias in low pay estimates. We consider how to correct for this bias when auxiliary accurately measured data are available for a subsample. An application to the UK Labour Force Survey is described. The use of fractional imputation, nearest neighbour imputation, predictive mean matching and propensity score weighting are considered. Properties of point estimators are compared both theoretically and by simulation. A fractional predictive mean matching imputation approach is advocated. It performs similarly to propensity score weighting, but displays slight advantages of robustness and efficiency.

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从住户调查数据估计时薪分布:利用缺失数据方法处理测量误差

小时工资调查数据中的测量误差可能导致低工资估计中的严重向上偏差。我们考虑当辅助精确测量数据可用于子样本时如何纠正这种偏差。应用到英国劳动力调查描述。考虑了分数归算、最近邻归算、预测均值匹配和倾向得分加权的使用。从理论和仿真两方面比较了点估计器的性质。提出了一种分数预测均值匹配插值方法。它的执行类似于倾向得分加权，但显示出鲁棒性和效率的轻微优势。

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

Survey Methodology 数学-统计学与概率论

CiteScore

0.80

自引率

22.20%

发文量

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.