Estimation of Response Propensities Using the Previous Survey

Miika Honkala
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Abstract

Many surveys are carried out yearly, and the implementation of the surveys remains the same from year to year. Experience from a previous survey is useful when planning a new survey, because the response behavior usually remains quite the same in subsequent years. This paper studies how response propensities, estimated using the dataset of the previous survey, predict actual response rates. In this study, two consecutive datasets of the European Social Survey were available. The both datasets contained same register variables. Response propensities were estimated to the older dataset using a logistic regression model. Then the propensities were imputed to the newer dataset using a donor-recipient method. The imputation was based on the explanatory variables of the logistic regression model so that the donor and the recipient had the same values in the variables. Then it was examined if there was a connection between the imputed response propensities and actual response rates. The result was that the imputed response propensities predicted the response behavior quite well. People with low response propensities were often nonrespondents, and people with high response propensities were often respondents. Using the previous survey, it is possible to calculate response propensities for a new sample before the data collection of the survey has been started. Then challenging respondents are known before the data collection, and this information is useful for data collection.
利用先前的调查估计反应倾向
许多调查是每年进行的,调查的执行情况每年都是一样的。以前调查的经验在计划新的调查时是有用的,因为在随后的几年里,反应行为通常保持不变。本文研究了使用先前调查的数据集估计的响应倾向如何预测实际响应率。在本研究中,欧洲社会调查的两个连续数据集是可用的。这两个数据集包含相同的寄存器变量。使用逻辑回归模型估计旧数据集的响应倾向。然后使用供体-受体方法将这些倾向输入到较新的数据集。在逻辑回归模型的解释变量基础上进行输入,使供体和受体在变量中具有相同的值。然后,它被检查是否有一个连接之间的估算反应倾向和实际反应率。结果表明,输入的反应倾向能很好地预测反应行为。低反应倾向的人通常是非应答者,而高反应倾向的人通常是应答者。使用以前的调查,可以在调查的数据收集开始之前计算新样本的响应倾向。然后在数据收集之前知道具有挑战性的受访者,这些信息对数据收集很有用。
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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