Abstract Sample surveys are often affected by nonresponse. These surveys have in common that their outcomes depend at least partly on a human decision whether or not to participate. If it would be completely clear how this decision mechanism works, estimates could be corrected. An often used approach is to introduce the concept of the response probability. Of course, these probabilities are a theoretical concept and therefore unknown. The idea is to estimate them by using the available data. If it is possible to obtain good estimates of the response probabilities, they can be used to improve estimators of population characteristics. Estimating response probabilities relies heavily on the use of models. An often used model is the logit model. In the article, this model is compared with the simple linear model. Estimation of response probabilities models requires the individual values of the auxiliary variables to be available for both the respondents and the nonrespondents of the survey. Unfortunately, this is often not the case. This article explores some approaches for estimating response probabilities that have less heavy data requirements. The estimated response probabilities were also used to measure possible deviations from representativity of the survey response. The indicator used is the coefficient of variation (CV) of the response probabilities.

中文翻译：

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处理响应概率

摘要样本调查通常会受到不答复的影响。这些调查的共同点是其结果至少部分取决于人为决定是否参与的决定。如果完全清楚此决策机制的工作原理，则可以对估计值进行更正。一种常用的方法是引入响应概率的概念。当然，这些概率是一个理论概念，因此是未知的。想法是通过使用可用数据来估计它们。如果有可能获得对响应概率的良好估计，则可以将其用于改进总体特征的估计。估计响应概率在很大程度上取决于模型的使用。经常使用的模型是logit模型。在本文中，将该模型与简单线性模型进行了比较。响应概率模型的估计要求辅助变量的各个值对调查的响应者和非响应者均可用。不幸的是，情况往往并非如此。本文探讨了一些估算数据需求较少的方法来估计响应概率的方法。估计的响应概率也用于测量与调查响应的代表性之间的可能偏差。使用的指标是响应概率的变异系数（CV）。估计的响应概率还用于测量与调查响应的代表性之间的可能偏差。使用的指标是响应概率的变异系数（CV）。估计的响应概率也用于测量与调查响应的代表性之间的可能偏差。使用的指标是响应概率的变异系数（CV）。