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Donor-based imputation methods for admin data: How to replace the number of rooms question on the Census

机译:管理数据的捐助者的估算方法:如何更换人口普查的房间数量

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摘要

The Census White Paper recommends removing the number of rooms question and to utilise administrative data instead. Previous research demonstrated that Valuation Office Agency (VOA) data can be used for this purpose in principal. However, users of Census micro-level data expect a utility dataset without missingness.This research project explored whether VOA number of rooms variable is suitable to undergo edit and imputation (E&I) within the standard census framework (i.e. donor imputation). We examined how linked admin and survey data challenges assumptions underlying the E&I process. We linked the 2011 Census with VOA data and attempted to impute VOA number of rooms using auxiliary variables from the Census to predict the missing and inconsistent values. This includes the question of whether we should allow questionnaire data to be changed where they are inconsistent with admin data.We demonstrated that it is possible to predict VOA number of rooms from census variables, despite some assumptions being partially violated (definitional and time-frame issues, the possibility of subpopulations in the data). This was true for missingness prior to linkage and missingness due to a data linkage failure. Additionally, we successfully tested the design principal of favouring survey data over alternative data where the two are inconsistent.We observed that some local authorities had large percentages of imputed data, and there was an increase in the percentage of properties where VOA number of rooms was equal to census number of bedrooms. This affects end-user interpretation of the data.The result is not a general endorsement that all linked survey-admin data can be effectively treated by standard E&I procedures. However, our research can be used as a blue print for other proof-of-concept studies on imputing admin data.
机译:人口普查白皮书建议删除房间数量问题并使用管理数据。以前的研究表明,估值办公室(VOA)数据可用于本国委托人。但是,人口普查微级数据的用户期望一个没有遗失的实用程序数据集。本研究项目探讨了VOA数量变量是否适合在标准人口普查框架内进行编辑和归因(E&I)(即捐赠者归属)。我们审查了如何链接的管理员和调查数据如何挑战E&i流程潜在的假设。我们将2011年人口普查与VOA数据联系起来,并尝试使用人口普查中的辅助变量赋予VOA数量,以预测丢失和不一致的值。这包括我们是否应该允许调查问卷数据更改的问题,在它们与管理数据不一致的情况下。我们证明,尽管部分违反了(定义和时帧问题,数据中子位常调的可能性,但是可以预测来自人口普查变量的VOA数量的房间数量。由于数据联动失败,在联系和缺失之前,这是如此。此外,我们成功地测试了替代数据的青睐调查数据的设计主体,其中两个是不一致的。我们观察到,一些地方当局有大量的估算数据,并且房间数量等于卧室的人口普查数量的物业百分比增加。这会影响数据的最终用户解释。结果不是一般的认可,即所有链接的调查管理员数据都可以通过标准E&I程序有效处理。然而,我们的研究可以用作抵御管理数据的其他概念证明研究的蓝色印刷品。

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