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Statistical Matching as a Supplement to Record Linkage: A Valuable Method to Tackle Nonconsent Bias?


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Andridge, R.R. and R.J. Little. 2010. “A Review of Hot Deck Imputation for Survey Non-response.” International Statistical Review 78(1): 40–64.10.1111/j.1751-5823.2010.00103.x313033821743766Search in Google Scholar

Antoni, M., A. Ganzer, and P. vom Berge. 2016. Sample of Integrated Labour Market Biographies (SIAB) 1975–2014. FDZ-Datenreport 4, Institute for Employment Research, Nuremberg, Germany. Avaiable at: http://doku.iab.de/fdz/reporte/2016/DR_04-16_EN.pdf.Search in Google Scholar

Antoni, M. and S. Seth. 2011. ALWA-ADIAB – linked individual survey and administrative data for substantive and methodological research. FDZ-Methodenreport 12, Institute for Employment Research, Nuremberg, Germany. Avaiable at: http://doku.iab.de/fdz/reporte/2011/DR_05-11.pdf.Search in Google Scholar

Biemer, P.P., R.M. Groves, L.E. Lyberg, N.A. Mathiowetz and S. Sudman. 2011. Measurement Errors in Surveys. John Wiley & Sons.Search in Google Scholar

Blossfeld, H.-P., H-G. Roßbach, and J. Von Maurice. 2011. “Education as a Lifelong Process.” Zeitschrift für Erziehungswissenschaft Sonderheft 14. ISBN: 978-3-531-17785-4.10.1007/s11618-011-0198-zSearch in Google Scholar

Brick, J.M. and G. Kalton. 1996. “Handling Missing Data in Survey Research.” Statistical Methods in Medical Research 5(3): 215 –238. Doi: http://dx.doi.org/10.1177/096228029600500302.10.1177/0962280296005003028931194Search in Google Scholar

Brücker, H., M. Kroh, S. Bartsch, J. Goebel, S. Kühne, E. Liebau, P. Trübswetter, I. Tucci and J. Schupp. 2014. “The New IAB-SOEP Migration Sample: An Introduction into the Methodology and the Contents.” SOEP Survey Papers 216. Avaiable at: http://hdl.handle.net/10419/103964.Search in Google Scholar

Calderwood, L. and C. Lessof. 2009. “Enhancing Longitudinal Surveys By Linking to Administrative Data.” In Methodology of Longitudinal Surveys, edited by P. Lynn, 55–72. New York: Wiley. ISBN: 978-0-470-01871-2.10.1002/9780470743874.ch4Search in Google Scholar

Chen, J. and J. Shao. 2000. “Nearest Neighbor Imputation for Survey Data.” Journal of Official Statistics 16(2): 113–131. Available at: https://www.scb.se/contentassets/ca21efb41fee47d293bbee5bf7be7fb3/nearest-neighbor-imputation-for-survey-data.pdf.Search in Google Scholar

Conti, P.L., D. Marella and M. Scanu. 2012. “Uncertainty Analysis in Statistical Matching.” Journal of Official Statistics 28(1): 69–88. Available at: https://www.scb.se/contentassets/ca21efb41fee47d293bbee5bf7be7fb3/uncertainty-analysis-in-statistical-matching.pdf.Search in Google Scholar

Conti, P.L., D. Marella and M. Scanu. 2016. “Statistical Matching Analysis for Complex Survey Data with Applications.” Journal of the American Statistical Association 111(516): 1715–1725. Doi: http://dx.doi.org/01621459.2015.1112803.10.1080/01621459.2015.1112803Search in Google Scholar

Cox, D.R. and D. Oakes. 1984. Analysis of Survival Data. CRC Press.Search in Google Scholar

da Silva, M.E.M., C.M. Coeli, M. Ventura, M. Palacios, M.M.F. Magnanini, T.M.C.R. Camargo and K.R. Camargo. 2012. “Informed Consent for Record Linkage: A Systematic Review.” Journal of Medical Ethics 38(10): 639 – 642. Doi: http://dx.doi.org/10.1136/medethics-2011-100208.10.1136/medethics-2011-10020822403083Search in Google Scholar

D’Orazio, M., M. Di Zio and M. Scanu. 2006a. “Statistical Matching for Categorical Data: Displaying Uncertainty using Logical Constraints.” Journal of Official Statistics 28(1): 137 – 157. Available at: https://www.scb.se/contentassets/ca21efb41fee47d293bbee5bf7be7fb3/statistical-matching-for-categorical-data-displaying-uncertainty-and-using-logical-constraints.pdf.Search in Google Scholar

D’Orazio, M., M. Di Zio and M. Scanu. 2006b. Statistical Matching: Theory and Practice. John Wiley & Sons.10.1002/0470023554Search in Google Scholar

D’Orazio, M., M. Di Zio and M. Scanu. 2009. “Uncertainty Intervals for Nonidentifiable Parameters in Statistical Matching.” Proceedings of the 57th session of the International Statistical Institute, August 16–22, 2009, Durban, South Africa.Search in Google Scholar

Fellegi, I.P. and A.B. Sunter. 1969. “A Theory for Record Linkage.” Journal of the American Statistical Association 64(328): 1183 – 1210. Doi: http://dx.doi.org/10.1080/01621459.1969.10501049.10.1080/01621459.1969.10501049Search in Google Scholar

Filippello, R., U. Guarnera and G. Jonas Lasinio. 2004. “Use of auxiliary information in statistical matching.” Proceedings of the XLII Conference of the Italian Statistical 9–11 June 2014, Bari, Italy: 37–40.Search in Google Scholar

Fosdick, B.K., M. DeYoreo and J.P. Reiter. 2016. “Categorical Data Fusion using Auxiliary Information.” The Annals of Applied Statistics 10(4): 1907–1929. Doi: http://dx.doi.org/10.1214/16-AOAS925.10.1214/16-AOAS925Search in Google Scholar

Fulton, J.A. 2012. Respondent Consent to Use Administrative Data, Ph. D. thesis, University of Maryland.Search in Google Scholar

GDPR. 2016. “Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation).” Official Journal of the European Union L119: 1–88. Available at: https://eur-lex.europa.eu/eli/reg/2016/679/oj.Search in Google Scholar

Gilula, Z. and R. McCulloch. 2013. “Multi Level Categorical Data Fusion using Partially Fused Data.” Quantitative Marketing and Economics 11(3): 353 – 377. Doi: http://dx.doi.org/10.1007/s11129-013-9136-0.10.1007/s11129-013-9136-0Search in Google Scholar

Gilula, Z., R.E. McCulloch and P.E. Rossi. 2006. “A Direct Approach to Data Fusion.” Journal of Marketing Research 43(1): 73–83. Doi: http://dx.doi.org/10.1509/jmkr.43.1.73.10.1509/jmkr.43.1.73Search in Google Scholar

Herzog, T.N., F.J. Scheuren and W.E. Winkler. 2007. Data Quality and Record Linkage Techniques. Springer Science & Business Media.Search in Google Scholar

Jacobebbinghaus, P. and S. Seth. 2010. Linked-Employer-Employee-Daten des IAB: LIAB – Querschnittmodell 2, 1993–2008. FDZ-Datenreport, Institute for Employment Research, Nuremberg, Germany.Search in Google Scholar

Jenkins, S.P., L. Cappellari, P. Lynn, A. Jäckle and E. Sala. 2006. “Patterns of Consent: Evidence from a General Household Survey.” Journal of the Royal Statistical Society: Series A (Statistics in Society) 169(4): 701–722. Doi: http://dx.doi.org/10.1111/j.1467-985X.2006.00417.x.10.1111/j.1467-985X.2006.00417.xSearch in Google Scholar

Kadane, J.B. 1978. “Some Statistical Problems in Merging Data Files.” Compendium of Tax Research, 159–179, Reprint in Journal of Official Statistics 17(3): 423–433. Avaiable at: https://www.scb.se/contentassets/ff271eeeca694f47ae99b942de61df83/some-statistical-problems-in-merging-data-files.pdf.Search in Google Scholar

Kreuter, F., J.W. Sakshaug and R. Tourangeau. 2016. “The Framing of the Record Linkage Consent Question.” International Journal of Public Opinion Research 28(1): 142–152. Doi: http://dx.doi.org/10.1093/ijpor/edv006.10.1093/ijpor/edv006Search in Google Scholar

Little, R.J. and D.B. Rubin. 2002. Statistical Analysis with Missing Data, (2nd ed.). John Wiley & Sons.10.1002/9781119013563Search in Google Scholar

Meinfelder, F. 2013. “Datenfusion: Theoretische Implikationen und praktische Umsetzung.” In Weiterentwicklung der amtlichen Haushaltsstatistiken, edited by T. Riede, N. Ott and S. Bechthold, 83–98. Berlin: GWI Wissenschaftspolitik Infrastrukturentwicklung.Search in Google Scholar

Moriarity, C. and F. Scheuren. 2001. “Statistical Matching: A Paradigm for Assessing the Uncertainty in the Procedure.” Journal of Official Statistics 17(3): 407–422. Available at: https://www.scb.se/contentassets/ca21efb41fee47d293bbee5bf7be7fb3/statistical-matching-a-paradigm-for-assessing-the-uncertainty-in-the-procedure.pdf.Search in Google Scholar

Moriarity, C. and F. Scheuren. 2003. “A Note On Rubin’s Statistical Matching using File Concatenation.” Journal of Business and Economic Statistics (21): 65–73. Doi: http://dx.doi.org/10.1198/073500102288618766.10.1198/073500102288618766Search in Google Scholar

Mostafa, T. 2016. “Variation within Households in Consent to Link Survey Data to Administrative Records: Evidence from the UK Millennium Cohort Study.” International Journal of Social Research Methodology 19(3): 355–375. Doi: http://dx.doi.org/10.1080/13645579.2015.1019264.10.1080/13645579.2015.1019264Search in Google Scholar

Ness, A.R. 2004. “The Avon Longitudinal Study of Parents and Children (ALSPAC) – A Resource for the Study of the Environmental Determinants of Childhood Obesity.” European Journal of Endocrinology 151(Suppl 3): U141–U149. Doi: http://dx.doi.org/10.1530/eje.0.151u141.10.1530/eje.0.151u14115554899Search in Google Scholar

Oberski, D.L., A. Kirchner, S. Eckman and F. Kreuter. 2017. “Evaluating the Quality of Survey and Administrative Data with Generalized Multitrait-Multimethod Models.” Journal of the American Statistical Association. Doi: http://dx.doi.org/10.1080/01621459.2017.1302338.10.1080/01621459.2017.1302338Search in Google Scholar

Paass, G. 1985. “Statistical Record Linkage Methodology: State of the Art and Future Prospects.” Bulletin of the International Statistical Society. Proceedings of the 45th Session. Voorburg, Netherlands: ISI.Search in Google Scholar

Rässler, S. 2002. Statistical Matching: A Frequentist Theory, Practical Applications, and Alternative Bayesian Approaches. Springer Science & Business Media.10.1007/978-1-4613-0053-3_2Search in Google Scholar

Rässler, S. 2003. “A Non-Iterative Bayesian Approach to Statistical Matching.” Statistica Neerlandica 57(1): 58–74. Doi: http://dx.doi.org/10.1111/1467-9574.00221.10.1111/1467-9574.00221Search in Google Scholar

Rässler, S. and H. Kiesl. 2009. “How Useful are Uncertainty Bounds? Some Recent Theory with an Application to Rubin’s Causal Model.” Proceedings of the 57th Session of the International Statistical Institute, August 16–22, 2009, Durban, South Africa. Available at https://www.isi-web.org/index.php/publications/proceedings.Search in Google Scholar

Renssen, R.H. 1998. “Use of Statistical Matching Techniques in Calibration Estimation.” Survey Methodology 24: 171–184. Available at: https://www150.statcan.gc.ca/n1/pub/12-001-x/1998002/article/4354-eng.pdf.Search in Google Scholar

Rodgers, W.L. 1984. “An Evaluation of Statistical Matching.” Journal of Business & Economic Statistics 2(1): 91 – 102. Doi: http://dx.doi.org/10.1080/07350015.1984.10509373.10.1080/07350015.1984.10509373Search in Google Scholar

Rubin, D.B. 1976. “Inference and Missing Data.” Biometrika (3): 581–592. Doi: http://dx.doi.org/10.2307/2335739.10.2307/2335739Search in Google Scholar

Rubin, D.B. 1978. “Multiple Imputation in Sample Surveys – a Phenomological Bayesian Approach to Nonresponse.” Proceedings of the Survey Research Method Section of the American Statistical Association: Joint Statistical Meetings 1978, San Diego, U.S.A.: 20–30. Available at: http://www.asasrms.org/Proceedings/index.html.Search in Google Scholar

Rubin, D.B. 1986. “Statistical Matching using File Concatenation with Adjusted Weights and Multiple Imputations.” Journal of Business & Economic Statistics 4(1): 87–94. Doi: http://dx.doi.org/10.1080/07350015.1986.10509497.10.1080/07350015.1986.10509497Search in Google Scholar

Rubin, D.B. 1987. Multiple Imputation for Nonresponse in Surveys. Wiley.10.1002/9780470316696Search in Google Scholar

Sakshaug, J.W., M.P. Couper, M.B. Ofstedal and D.R. Weir. 2012. “Linking Survey and Administrative Records: Mechanisms of Consent.” Sociological Methods & Research 41(4): 535–569. Doi: http://dx.doi.org/10.1177/0049124112460381.10.1177/0049124112460381492863527375305Search in Google Scholar

Sakshaug, J.W. and M. Huber. 2016. “An Evaluation of Panel Nonresponse and Linkage Consent Bias in a Survey of Employees in Germany.” Journal of Survey Statistics and Methodology 4(1): 71–93. Doi: http://dx.doi.org/10.1093/jssam/smv034.10.1093/jssam/smv034Search in Google Scholar

Sakshaug, J.W., S. Hülle, A. Schmucker and S. Liebig. 2017. “Exploring the Effects of Interviewer- and Self-administered Survey Modes on Record Linkage Consent Rates and Bias.” Survey Research Methods 11(forthcoming): 171 – 188. Doi: http://dx.doi.org/10.18148/srm/2017.v11i2.7158.Search in Google Scholar

Sakshaug, J.W. and F. Kreuter. 2012. “Assessing the Magnitude of Non-Consent Biases in Linked Survey and Administrative Data.” Survey Research Methods 6(2): 113–122. Doi: http://dx.doi.org/10.18148/srm/2012.v6i2.5094.Search in Google Scholar

Sakshaug, J.W. and B. Vicari. 2017. “Obtaining Record Linkage Consent from Establishments: The Impact of Question Placement on Consent Rates and Bias.” Journal of Survey Statistics and Methodology.Doi: http://dx.doi.org/10.1093/jssam/smx009.10.1093/jssam/smx009Search in Google Scholar

Sala, E., J. Burton and G. Knies. 2012. “Correlates of Obtaining Informed Consent to Data Linkage: Respondent, Interview, and Interviewer Characteristics.” Sociological Methods & Research 41(3): 414– 439. Doi: http://dx.doi.org/10.1177/0049124112457330.10.1177/0049124112457330Search in Google Scholar

Schulte Nordholt, E., J. Van Zeijl and L. Hoeksma. 2014. Dutch Census 2011, Analysis and Methodology, Technical report, Statistics Netherlands. ISBN: 978-90-357-1948-4. Available at: https://www.cbs.nl/NR/rdonlyres/5FDCE1B4-0654-45DA-8D7E-807A0213DE66/0/2014b57pub.pdf.Search in Google Scholar

Sims, C. 1972. “Comments on Okner (1972).” Annals of Economic and Social Measurement (1): 343–345.Search in Google Scholar

Singh, A., H. Mantel, M. Kinack and G. Rowe. 1993. “Statistical Matching: Use of Auxiliary Information as an Alternative to the Conditional Independence Assumption.” Survey Methodology 19(1): 59–79. Available at: https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X199300114475.Search in Google Scholar

Sozialgesetzbuch. 1997. SGB Drittes Buch (III) – “Arbeitsförderung”.Search in Google Scholar

Sozialgesetzbuch. 2003. SGB Zweites Buch (II) – “Grundsicherung für Arbeitsuchende”.Search in Google Scholar

Trappmann, M., J. Beste, A. Bethmann and G. Müller. 2013. “The PASS Panel Survey After Six Waves.” Journal for Labour Market Research 46(4): 275–281. Doi: http://dx.doi.org/10.1007/s12651-013-0150-1.10.1007/s12651-013-0150-1Search in Google Scholar

Van Buuren, S. and K. Groothuis-Oudshoorn. 2011. “MICE: Multivariate Imputation By Chained Equations in R.” Journal of Statistical Software 45(3). Doi: http://dx.doi.org/10.18637/jss.v045.i03.10.18637/jss.v045.i03Search in Google Scholar

Wu, C. 2004. “Combining Information from Multiple Surveys through the Empirical Likelihood Method.” Canadian Journal of Statistics 32(1): 15 – 26. Doi: http://dx.doi.org/10.2307/3315996.10.2307/3315996Search in Google Scholar

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