数据清洗管道入门

IF 1.6 4区 数学 Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS
Rebecca C Steorts
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引用次数: 1

摘要

结构化和非结构化数据库的可用性,如电子健康数据、社交媒体数据、专利数据和经常实时更新的调查等,在过去十年中迅速增长。随着这种扩展,围绕数据集成(或者说合并多个数据源)的统计和方法问题也在增加。具体来说,“数据清理管道”包含四个阶段,允许分析人员执行下游任务、预测分析或对“已清理数据”进行统计分析。本文综述了这一新兴领域,介绍了技术术语和常用方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Primer on the Data Cleaning Pipeline
Abstract The availability of both structured and unstructured databases, such as electronic health data, social media data, patent data, and surveys that are often updated in real time, among others, has grown rapidly over the past decade. With this expansion, the statistical and methodological questions around data integration, or rather merging multiple data sources, have also grown. Specifically, the science of the “data cleaning pipeline” contains four stages that allow an analyst to perform downstream tasks, predictive analyses, or statistical analyses on “cleaned data.” This article provides a review of this emerging field, introducing technical terminology and commonly used methods.
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来源期刊
CiteScore
4.30
自引率
9.50%
发文量
40
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.
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