[Boonstra, H. (2004). A simulation study of repeated weighting estimation. Voorburg/Heerlen: Statistics Netherlands.]Search in Google Scholar
[Boonstra, H., van den Brakel, J., Knottnerus, P., Nieuwenbroek, N., & Renssen, R. (2003). Dacseis deliverable 7.2: A strategy to obtain consistency among tables of survey estimates. Heerlen: Statistics Netherlands.]Search in Google Scholar
[Chambers, R., & Diniz da Silva, A. (2020). Improved secondary analysis of linked data: A framework and an illustration. Journal of the Royal Statistical Society: Series A (Statistics in Society), 183(1), 37-59.10.1111/rssa.12477]Search in Google Scholar
[De Waal, T. (2016). Obtaining numerically consistent estimates from a mix of administrative data and surveys. Statistical Journal of the IAOS, 32(2), 231-243.10.3233/SJI-150950]Search in Google Scholar
[De Waal, T., van Delden, A., & Scholtus, S. (2020). Multi-source statistics: Basic situations and methods. International Statistical Review, 88(1), 203-228.10.1111/insr.12352]Search in Google Scholar
[Deville, J.-C., & Särndal, C.-E. (1992). Calibration estimators in survey sampling. Journal of the American Statistical Association, 87(418), 376-382.10.1080/01621459.1992.10475217]Search in Google Scholar
[Harron, K., Goldstein, H., & Dibben, C. (2015). Methodological developments in data linkage. Hoboken: John Wiley & Sons.10.1002/9781119072454]Search in Google Scholar
[Haziza, D., & Lesage, É. (2016). A discussion of weighting procedures for unit nonresponse. Journal of Official Statistics, 32(1), 129-145.10.1515/jos-2016-0006]Search in Google Scholar
[Houbiers, M. (2004). Towards a social statistical database and unified estimates at Statistics Netherlands. Journal of Official Statistics, 20(1), 55.]Search in Google Scholar
[Houbiers, M., Knottnerus, P., Kroese, A., Renssen, R., & Snijders, V. (2003). Estimating consistent table sets: Position paper on repeated weighting. (Statistics Netherlands, Discussion Paper, No. 3005).]Search in Google Scholar
[Kalton, G., & Flores-Cervantes, I. (2003). Weighting methods. Journal of Official Statistics, 19(2), 81.]Search in Google Scholar
[Knottnerus, P., & van Duin, C. (2006). Variances in repeated weighting with an application to the dutch labour force survey. Journal of Official Statistics, 22(3), 565.]Search in Google Scholar
[Kott, P. S. (2006). Using calibration weighting to adjust for nonresponse and coverage errors. Survey Methodology, 32(2), 133.]Search in Google Scholar
[Kott, P. S., & Chang, T. (2010). Using calibration weighting to adjust for nonignorable unit nonresponse. Journal of the American Statistical Association, 105(491), 1265-1275.10.1198/jasa.2010.tm09016]Search in Google Scholar
[Kroese, A., & Renssen, R. (1999). Weighting and imputation at Statistics Netherlands. (Proceedings of the IASS conference on Small Area Estimation, Riga August 1999, 109-120).]Search in Google Scholar
[Lundström, S., & Särndal, C.-E. (1999). Calibration as a standard method for treatment of nonresponse. Journal of Official Statistics, 15(2), 305.]Search in Google Scholar
[Luppes, M., & Nielsen, P. B. (2020). Micro data linking: Addressing new emerging topics without increasing the respondent burden. Statistical Journal of the IAOS, 1-13.10.3233/SJI-200679]Search in Google Scholar
[Nordholt, E. S. (2005). The Dutch virtual census 2001: A new approach by combining different sources. Statistical Journal of the United Nations Economic Commission for Europe, 22(1), 25-37.10.3233/SJU-2005-22104]Search in Google Scholar
[Nordholt, E. S., van Zeijl, J., & Hoeksma, L. (2014). Dutch Census 2011: Analysis and Methodology. The Hague / Heerlen: Statistics Netherlands.]Search in Google Scholar
[R Core Team. (2019). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.]Search in Google Scholar
[Rässler, S. (2012). Statistical matching: A frequentist theory, practical applications, and alternative Bayesian approaches (vol. 168). New York: Springer Science & Business Media.]Search in Google Scholar
[Renssen, R., Kroese, A., & Willeboordse, A. (2001). Aligning estimates by repeated weighting. Heerlen: Statistics Netherlands.]Search in Google Scholar
[Roszka, W. (2013). Statystyczna integracja danych w badaniach społeczno-ekonomicznych. (Unpublished doctoral dissertation). Poznań: Poznań University of Economics and Business.]Search in Google Scholar
[Särndal, C.-E. (2007). The calibration approach in survey theory and practice. Survey Methodology, 33(2), 99-119.]Search in Google Scholar
[Särndal, C.-E., & Lundström, S. (2005). Estimation in surveys with nonresponse. Hoboken: John Wiley & Sons.10.1002/0470011351]Search in Google Scholar
[Sayers, A., Ben-Shlomo, Y., Blom, A. W., & Steele, F. (2016). Probabilistic record linkage. International Journal of Epidemiology, 45(3), 954-964.10.1093/ije/dyv322]Search in Google Scholar
[Statistics Poland. (2014). The methodology of THE 2011 National Population and Housing Census: Selected aspects.]Search in Google Scholar
[Szymkowiak, M. (2019). Podejście kalibracyjne w badaniach społeczno-ekonomicznych. Poznań: Wydawnictwo Uniwersytetu Ekonomicznego w Poznaniu.]Search in Google Scholar
[Van der Laan, J. (2018). Reclin: record linkage toolkit. R package version 0.1.1. Retrieved from https://cran.r-project.org/web/packages/reclin/reclin.pdf]Search in Google Scholar
[Wu, C. & Lu, W. W. (2016). Calibration weighting methods for complex surveys. International Statistical Review, 84(1), 79-98.10.1111/insr.12097]Search in Google Scholar
[Yang, S., & Kim, J. K. (2020). Statistical data integration in survey sampling: A review. Japanese Journal of Statistics and Data Science, 3, 625-650.10.1007/s42081-020-00093-w]Search in Google Scholar
[Zhang, L.-C., & Tuoto, T. (2020). Linkage-data linear regression. Journal of the Royal Statistical Society: Series A (Statistics in Society), 1-26.]Search in Google Scholar