Improving Probabilistic Record Linkage Using Statistical Prediction Models

Summary Record linkage brings together information from records in two or more data sources that are believed to belong the same statistical unit based on a common set of matching variables. Matching variables, however, can appear with errors and variations challenge is link units subject error. We provide an overview record techniques specifically investigate classic Fellegi Sunter probabilistic framework assess whether decision rule for classifying pairs into sets matches non‐matches be improved by incorporating prediction model. also study enhanced better results terms preserving associations between variables linked file not used procedure. A simulation application real evaluate methods.