Correlates of Record Linkage and Estimating Risks of Non-Linkage Biases in Business Data Sets
研究了2010年英国小企业调查数据中企业关联倾向的相关因素，首次区分同意关联和注册标识符可附加性，并引入数据集代表性指标评估非关联偏差风险，发现同意者与非同意者的差异及小微企业注册覆盖不足是主要偏差来源。
Summary Researchers often utilize data sets that link information from multiple sources, but non-linkage biases caused by linked and non-linked subject differences are little understood, especially in business data sets. We address these knowledge gaps by studying biases in linkable 2010 UK Small Business Survey data sets. We identify correlates of business linkage propensity, and also for the first time its components: consent to linkage and register identifier appendability. As well, we take a novel approach to evaluating non-linkage bias risks, by computing data set representativeness indicators (comparable, decomposable sample subset similarity measures). We find that the main impacts on linkage propensities and bias risks are due to consenter–non-consenter differences explicable given business survey response processes, and differences between subjects with and without identifiers caused by register undercoverage of very small businesses. We then discuss consequences for the analysis of linked business data sets, and implications of the evaluation methods we introduce for linked data set producers and users.