Model-based estimation of record linkage error rates

Record linkage is the matching of records containing data on individuals, businesses or dwellings when a unique identifier is not available. Methods used in practice involve classification of record pairs as links and non-links using an automated procedure based on the theoretical framework introduced by Fellegi and Sunter (1969). The estimation of classification error rates is an important issue. Fellegi and Sunter provide a method for calculation of classification error rate estimates as a direct by-product of linkage. These model-based estimates are easier to produce than the estimates based on manual matching of samples that are typically used in practice. Properties of model-based classification error rate estimates obtained using three estimators of model parameters are compared.