Regression analysis with linked data: problems and possible solutions
In this paper we have described and extended some recent proposals on a general Bayesian methodology for performing record linkage and making inference using the resulting matched units. In particular, we have framed the record linkage process into a formal statistical model which comprises both t...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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University of Bologna
2015-03-01
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| Series: | Statistica |
| Subjects: | |
| Online Access: | http://rivista-statistica.unibo.it/article/view/5821 |
| _version_ | 1819265008910991360 |
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| author | Andrea Tancredi Brunero Liseo |
| author_facet | Andrea Tancredi Brunero Liseo |
| author_sort | Andrea Tancredi |
| collection | DOAJ |
| description | In this paper we have described and extended some recent proposals on a general Bayesian methodology for performing record linkage and making inference using the resulting matched units. In particular, we have framed the record linkage process into a formal statistical model which comprises both the matching variables and the other variables included at the inferential stage. This way, the researcher is able to account for the matching process uncertainty in inferential procedures based on probabilistically linked data, and at the same time, he/she is also able to generate a feedback propagation of the information between the working statistical model and the record linkage stage.We have argued that this feedback effect is both essential to eliminate potential biases that otherwise would characterize the resulting linked data inference, and able to improve record linkage performances. The practical implementation of the procedure is based on the use of standard Bayesian computational techniques, such as Markov Chain Monte Carlo algorithms. Although the methodology is quite general, we have restricted our analysis to the popular and important case of multiple linear regression set-up for expository convenience. |
| first_indexed | 2024-12-23T20:38:33Z |
| format | Article |
| id | doaj.art-bf65f1f18258467fbca6a50bfc9a9a9d |
| institution | Directory Open Access Journal |
| issn | 0390-590X 1973-2201 |
| language | English |
| last_indexed | 2024-12-23T20:38:33Z |
| publishDate | 2015-03-01 |
| publisher | University of Bologna |
| record_format | Article |
| series | Statistica |
| spelling | doaj.art-bf65f1f18258467fbca6a50bfc9a9a9d2022-12-21T17:32:00ZengUniversity of BolognaStatistica0390-590X1973-22012015-03-01751193510.6092/issn.1973-2201/58215309Regression analysis with linked data: problems and possible solutionsAndrea Tancredi0Brunero Liseo1Università di Roma “La Sapienza”Università di Roma “La Sapienza”In this paper we have described and extended some recent proposals on a general Bayesian methodology for performing record linkage and making inference using the resulting matched units. In particular, we have framed the record linkage process into a formal statistical model which comprises both the matching variables and the other variables included at the inferential stage. This way, the researcher is able to account for the matching process uncertainty in inferential procedures based on probabilistically linked data, and at the same time, he/she is also able to generate a feedback propagation of the information between the working statistical model and the record linkage stage.We have argued that this feedback effect is both essential to eliminate potential biases that otherwise would characterize the resulting linked data inference, and able to improve record linkage performances. The practical implementation of the procedure is based on the use of standard Bayesian computational techniques, such as Markov Chain Monte Carlo algorithms. Although the methodology is quite general, we have restricted our analysis to the popular and important case of multiple linear regression set-up for expository convenience.http://rivista-statistica.unibo.it/article/view/5821Bayesian regressionHit-miss modelMetropolis-Hastings algorithmRecord linkage |
| spellingShingle | Andrea Tancredi Brunero Liseo Regression analysis with linked data: problems and possible solutions Statistica Bayesian regression Hit-miss model Metropolis-Hastings algorithm Record linkage |
| title | Regression analysis with linked data: problems and possible solutions |
| title_full | Regression analysis with linked data: problems and possible solutions |
| title_fullStr | Regression analysis with linked data: problems and possible solutions |
| title_full_unstemmed | Regression analysis with linked data: problems and possible solutions |
| title_short | Regression analysis with linked data: problems and possible solutions |
| title_sort | regression analysis with linked data problems and possible solutions |
| topic | Bayesian regression Hit-miss model Metropolis-Hastings algorithm Record linkage |
| url | http://rivista-statistica.unibo.it/article/view/5821 |
| work_keys_str_mv | AT andreatancredi regressionanalysiswithlinkeddataproblemsandpossiblesolutions AT bruneroliseo regressionanalysiswithlinkeddataproblemsandpossiblesolutions |