Common practice to address nonresponse in probability surveys in National Statistical Offices is to follow up every nonrespondent with a view to lifting response rates. As response rate is an insufficient indicator of data quality, it is argued that one should follow up nonrespondents with a view to reducing the mean squared error (MSE) of the estimator of the variable of interest. In this paper, we propose a method to allocate the nonresponse follow-up resources in such a way as to minimise the MSE under a quasi-randomisation framework. An example to illustrate the method using the 2018/19 Rural Environment and Agricultural Commodities Survey from the Australian Bureau of Statistics is provided.

翻译：国家统计局在概率调查中处理无应答的常见做法是对每位无应答者进行后续追踪以提高应答率。由于应答率并非数据质量的充分指标，本文主张应以减少目标变量估计量的均方误差为导向开展无应答追踪。本文提出一种方法，在拟随机化框架下通过配置无应答后续追踪资源以实现均方误差最小化。并以澳大利亚统计局2018/19年度农村环境与农产品调查数据为例说明该方法的应用。