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There is an increasing number of applications of record linkage in statistical, health, government and business organisations to link administrative, survey, population census and other files to create a complete set of information for more complete and comprehensive analysis. To make valid inferences using a linked file, it has become increasingly important to have effective and efficient methods for linking data from different sources. Therefore, it becomes necessary to assess the ability of a linking method to achieve high accuracy or to compare between methods with respect to accuracy. This motivates the development of a method for assessing the linking process and facilitating decisions about which linking method is likely to be more accurate for a particular linking task. This paper proposes a Markov Chain based Monte Carlo simulation approach, <jats:italic>MaCSim<\/jats:italic> for assessing a linking method and illustrates the utility of the approach using a realistic synthetic dataset received from the Australian Bureau of Statistics to avoid privacy issues associated with using real personal information. A linking method applied by <jats:italic>MaCSim<\/jats:italic> is also defined. To assess the defined linking method, correct re-link proportions for each record are calculated using our developed simulation approach. The accuracy is determined for a number of simulated datasets. The analyses indicated promising performance of the proposed method <jats:italic>MaCSim<\/jats:italic> of the assessment of accuracy of the linkages. The computational aspects of the methodology are also investigated to assess its feasibility for practical use.<\/jats:p>","DOI":"10.1186\/s40537-020-00394-7","type":"journal-article","created":{"date-parts":[[2021,1,6]],"date-time":"2021-01-06T22:03:01Z","timestamp":1609970581000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Assessing the accuracy of record linkages with Markov chain based Monte Carlo simulation approach"],"prefix":"10.1186","volume":"8","author":[{"given":"Shovanur","family":"Haque","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kerrie","family":"Mengersen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Steven","family":"Stern","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,1,6]]},"reference":[{"key":"394_CR1","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1111\/j.1467-9574.2011.00505.x","volume":"66","author":"BFM Bakker","year":"2012","unstructured":"Bakker BFM, Daas P. 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