Extending the Fellegi-Sunter record linkage model for mixed-type data with application to the French national health data system
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Publication:6111535
DOI10.1016/j.csda.2022.107656OpenAlexW3183610643MaRDI QIDQ6111535
André Happe, Guillaume Chauvet, Emmanuel Oger, Thanh Huan Vo, Valérie Garès, Stéphane Paquelet
Publication date: 7 July 2023
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2022.107656
mixture modelprobabilistic record linkageexpectation conditional maximization (ECM) algorithmhurdle gamma distributionlow prevalence variables
Cites Work
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- A hierarchical Bayesian approach to record linkage and population size problems
- On the convergence properties of the EM algorithm
- Regression analysis under incomplete linkage
- Incorporating conditional dependence in latent class models for probabilistic record linkage: does it matter?
- Maximum likelihood estimation via the ECM algorithm: A general framework
- Data Quality and Record Linkage Techniques
- A Method for Calibrating False-Match Rates in Record Linkage
- Encyclopedia of Machine Learning and Data Mining
- Regression Analysis With Linked Data
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