论文标题
从具有不可偿还的无反应的调查数据中推断出人口组成：从外部来源借用信息
Inferring a population composition from survey data with nonignorable nonresponse: Borrowing information from external sources
论文作者
论文摘要
我们介绍了一种使用调查数据来推断异质种群组成的方法，这说明了捕获异质性与关键调查变量有关的可能性。为了处理不可签署的无响应，我们将不同的数据源结合在一起，并提出在贝叶斯框架中使用Fisher非中性高几幅模型的使用。为了说明我们方法论的潜力，我们专注于一个案例研究，旨在通过毕业后一年来通过其职业地位来估算意大利毕业生人口的组成，按性别和学位课程进行分层。我们说明调查有关新毕业生职业状况的调查可能具有依赖个人就业状况的回应率，这意味着无响应的不可降价性。我们的发现表明，受雇人士通常更倾向于回答问卷。在这种情况下忽略了无响应偏见可能会导致高估就业率。
We introduce a method to make inference on the composition of a heterogeneous population using survey data, accounting for the possibility that capture heterogeneity is related to key survey variables. To deal with nonignorable nonresponse, we combine different data sources and propose the use of Fisher's noncentral hypergeometric model in a Bayesian framework. To illustrate the potentialities of our methodology, we focus on a case study aimed at estimating the composition of the population of Italian graduates by their occupational status one year after graduating, stratifying by gender and degree program. We account for the possibility that surveys inquiring about the occupational status of new graduates may have response rates that depend on individuals' employment status, implying the nonignorability of the nonresponse. Our findings show that employed people are generally more inclined to answer the questionnaire. Neglecting the nonresponse bias in such contexts might lead to overestimating the employment rate.
