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Estimating Classification Errors Under Edit Restrictions in Composite Survey-Register Data Using Multiple Imputation Latent Class Modelling (MILC)


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André, S. and C. Dewilde. 2016. “Home Ownership and Support for Government Redistribution.” Comparative European Politics 14: 319–348. Doi: http://dx.doi.org/10.1057/cep.2014.31.10.1057/cep.2014.31Open DOISearch in Google Scholar

Bakk, Z., D.L. Oberski, and J.K. Vermunt. 2016. “Relating Latent Class Membership to Continuous Distal Outcomes: Improving the LTB Approach and a Modified Three-Step Implementation.” Structural Equation Modeling: A Multidisciplinary Journal 23: 278–289. Doi: http://dx.doi.org/10.1080/10705511.2015.1049698.10.1080/10705511.2015.1049698Open DOISearch in Google Scholar

Bakker, B.F.M. 2009. Trek alle registers open! Rede in verkorte vorm uitgesproken bij de aanvaarding van het ambt van bijzonder hoogleraar Methodologie van registers voor sociaalwetenschappelijk onderzoek bij de Faculteit der Sociale Wetenschappen van de Vrije Universiteit Amsterdam op 26 november 2009. Available at: http://dare.ubvu.vu.nl/bitstream/handle/1871/15588/Oratie%20Bakker.pdf (accessed April 24, 2017).Search in Google Scholar

Bakker, B.F.M. 2010. “Micro-Integration, State of the Art.” Paper presented at the joint UNECE-Eurostat expert group meeting on registered based censuses in The Hague, May 11, 2010. Available at: https://www.unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.41/2010/wp.10.e.pdf (accessed April 24, 2017).Search in Google Scholar

Bakker, B.F.M. 2012. “Estimating the Validity of Administrative Variables.” Statistica Neerlandica 66: 8–17. Doi: http://dx.doi.org/10.1111/j.14679574.2011.00504.x.10.1111/j.14679574.2011.00504.xOpen DOISearch in Google Scholar

Biemer, P.P. 2011. Latent Class Analysis of Survey Error (Vol. 571). Hoboken, New Jersey: John Wiley & Sons.10.1002/9780470891155Search 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: 231–243. Doi: http://dx.doi.org//10.3233/SJI-150950.10.3233/SJI-150950Open DOISearch in Google Scholar

De Waal, T., J. Pannekoek, and S. Scholtus. 2011. Handbook of Statistical Data Editing and Imputation (Vol. 563). John Wiley & Sons.10.1002/9780470904848Search in Google Scholar

De Waal, T., J. Pannekoek, and S. Scholtus. 2012. “The Editing of Statistical Data: Methods and Techniques for the Efficient Detection and Correction of Errors and Missing Values.” Wiley Interdisciplinary Reviews: Computational Statistics 4: 204–210. Doi: http://dx.doi.org/10.1002/wics.1194.10.1002/wics.1194Open DOISearch in Google Scholar

Dewilde, C. and P.D. Decker. 2016. “Changing Inequalities in Housing Outcomes Across Western Europe.” Housing, Theory and Society 33: 121–161. Doi: http://dx.doi.org/10.1080/14036096.2015.1109545.10.1080/14036096.2015.1109545Open DOISearch in Google Scholar

Dias, J.G. and J.K. Vermunt. 2008. “A Bootstrap-Based Aggregate Classifier for Model-Based Clustering.” Computational Statistics 23: 643–659. Doi: http://dx.doi.org/10.1007/s00180-007-0103-7.10.1007/s00180-007-0103-7Open DOISearch in Google Scholar

Forcina, A. 2008. “Identifiability of Extended Latent Class Models with Individual Covariates.” Computational Statistics & Data Analysis 52: 5263–5268. Doi: http://dx.doi.org/10.1016/j.csda.2008.04.030.10.1016/j.csda.2008.04.030Open DOISearch in Google Scholar

Geerdinck, M., M. Goedhuys-van der Linden, E. Hoogbruin, A. De Rijk, N. Sluiter, and C. Verkleij. 2014. Monitor Kwaliteit Stelsel van Basisregistraties: Nulmeting van de Kwaliteit van Basisregistraties in Samenhang, 2014 (13114th ed.). Henri Faas-dreef 312, 2492 JP Den Haag: Centraal Bureau voor de Statistiek. Available at: https://www.cbs.nl/-/media/pdf/2016/50/monitor-kwaliteit-stelsel-van-basisregistraties.pdf (accessed April 25, 2017).Search in Google Scholar

Groen, J.A. 2012. “Sources of Error in Survey and Administrative Data: The Importance of Reporting Procedures.” Journal of Official Statistics 28: 173–198.Search in Google Scholar

Guarnera, U. and R. Varriale. 2016. “Estimation from Contaminated Multi-Source Data Based on Latent Class Models.” Statistical Journal of the IAOS 32: 537–544. Doi: dx.doi.org//10.3233/SJI-150951.10.3233/SJI-150951Open DOISearch in Google Scholar

Jörgren, F., R. Johansson, L. Damber, and G. Lindmark. 2010. “Risk Factors of Rectal Cancer Local Recurrence: Population-Based Survey and Validation of the Swedish Rectal Cancer Registry.” Colorectal Disease 12: 977–986. Doi: http://dx.doi.org/10.1111/j.1463-1318.2009.01930.x.10.1111/j.1463-1318.2009.01930.x19438885Open DOISearch in Google Scholar

Kim, H.J., L.H. Cox, A.F. Karr, J.P. Reiter, and Q. Wang. 2015. “Simultaneous Edit-Imputation for Continuous Microdata.” Journal of the American Statistical Association 110: 987–999. Doi: http://dx.doi.org/10.1080/01621459.2015.1040881.10.1080/01621459.2015.1040881Open DOISearch in Google Scholar

Lersch, P.M. and C. Dewilde. 2015. “Employment Insecurity and First-Time Homeownership: Evidence from Twenty-Two European Countries.” Environment and Planning A 47: 607–624. Doi: http://dx.doi.org//10.1068/a130358p.10.1068/a130358pOpen DOISearch in Google Scholar

Manrique-Vallier, D. and J.P. Reiter. 2013. “Bayesian Multiple Imputation for Large-Scale Categorical Data with Structural Zeros.” Survey Methodology 40: 125–134. Available at: https://ecommons.cornell.edu/handle/1813/34889 (accessed April 25, 2017).Search in Google Scholar

Manrique-Vallier, D. and J.P. Reiter. 2016. “Bayesian Simultaneous Edit and Imputation for Multivariate Categorical Data.” Journal of the American Statistical Association. Doi: http://dx.doi.org/10.1080/01621459.2016.1231612.10.1080/01621459.2016.1231612Open DOISearch in Google Scholar

Mulder, C.H. 2006. “Home-Ownership and Family Formation.” Journal of Housing and the Built Environment 21: 281–298. Doi: http://dx.doi.org/10.1007/s10901-006-9050-9.10.1007/s10901-006-9050-9Open DOISearch 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.0.151U14115554899Open DOISearch in Google Scholar

Oberski, D.L. 2015. “Total Survey Error in Practice.” In Total Survey Error, edited by P.P. Biemer, E. de Leeuw, S. Eckman, B. Edwards, F. Kreuter, L. Lyberg, N. Tucker, and B. West. New York: Wiley.Search in Google Scholar

Pavlopoulos, D. and J. Vermunt. 2015. “Measuring Temporary Employment. Do Survey or Register Tell the Truth?” Survey Methodology 41: 197–214. Available at: http://www.statcan.gc.ca/pub/12-001-x/2015001/article/14151-eng.pdf (accessed April 25, 2017).Search in Google Scholar

R Core Team. 2014. “R: A Language and Environment for Statistical Computing [Computer software manual].” Vienna, Austria. Available at: http://www.R-project.org/ (accessed October 13, 2017).Search in Google Scholar

Robertsson, O., M. Dunbar, K. Knutson, S. Lewold, and L. Lidgren. 1999. “Validation of the Swedish Knee Arthroplasty Register: A Postal Survey Regarding 30,376 Knees Operated on Between 1975 and 1995.” Acta Orthopaedica Scandinavica 70: 467–472. Doi: http://dx.doi.org/10.3109/17453679909000982.10.3109/1745367990900098210622479Open DOISearch in Google Scholar

Rubin, D.B. 1987. Multiple Imputation for Nonresponse in Surveys (Vol. 81). John Wiley & Sons. Doi: http://dx.doi.org//10.1002/9780470316696.10.1002/9780470316696Open DOISearch in Google Scholar

Scherpenzeel, A. 2011. “Data Collection in a Probability-Based Internet Panel: How the LISS Panel was Built and How it can be Used.” Bulletin of Sociological Methodology/Bulletin de Methodologie Sociologique 109: 56–61. Doi: http://dx.doi.org//10.1177/0759106310387713.10.1177/0759106310387713Open DOISearch in Google Scholar

Scholtus, S. 2009. “Automatic Detection of Simple Typing Errors in Numerical Data with Balance Edits.” Statistics Netherlands Discussion Paper (09046). Available at: https://www.cbs.nl/-/media/imported/documents/2009/48/2009-46-x10-pub.pdf (accessed April 25, 2017).Search in Google Scholar

Scholtus, S. 2011. “Algorithms for Correcting Sign Errors and Rounding Errors in Business Survey Data.” Journal of Official Statistics 27: 467–490.Search in Google Scholar

Scholtus, S. and B.F.M. Bakker. 2013. “Estimating the Validity of Administrative and Survey Variables through Structural Equation Modeling: A Simulation Study on Robustness.” Statistics Netherlands Discussion Paper. Available at: https://www.cbs.nl/-/media/imported/documents/2013/12/2013-02-x10-pub.pdf (accessed April 25, 2017).Search in Google Scholar

Schrijvers, C.T.M., K. Stronks, D.H. van de Mheen, J.-W. W. Coebergh, and J.P. Mackenbach. 1994. “Validation of Cancer Prevalence Data from a Postal Survey by Comparison with Cancer Registry Records.” American Journal of Epidemiology 139: 408–414. Doi: https://doi.org/10.1093/oxfordjournals.aje.a117013.10.1093/oxfordjournals.aje.a1170138109575Open DOISearch in Google Scholar

Schulte Nordholt, E., J. Van Zeijl, and L. Hoeksma. 2014. “Dutch Census 2011, Analysis and Methodology.” Statistics Netherlands. Available at: https://www.cbs.nl/-/media/imported/documents/2014/44/2014-b57-pub.pdf (accessed April 25, 2017).Search in Google Scholar

Si, Y. and J.P. Reiter. 2013. “Nonparametric Bayesian Multiple Imputation for Incomplete Categorical Variables in Large-Scale Assessment Surveys.” Journal of Educational and Behavioral Statistics 38: 499–521. Doi: dx.doi.org//10.3102/1076998613480394.10.3102/1076998613480394Open DOISearch in Google Scholar

Tempelman, C. 2007. Imputation of Restricted Data: Applications to Business surveys (Doctoral dissertation, Rijksuniversiteit Groningen). Available at: https://www.cbs.nl/-/media/imported/documents/2007/05/2007-i76-pub.pdf (accessed April 25, 2017).Search in Google Scholar

Turner, C.F., T.K. Smith, L.K. Fitterman, T. Reilly, K. Pate, M.B. Witt, and B.H. Forsyth. 1997. “The Quality of Health Data Obtained in a New Survey of Elderly Americans: A Validation Study of the Proposed Medicare Beneficiary Health Status Registry (mbhsr).” The Journals of Gerontology Series B: Psychological Sciences and Social Sciences 52B: S49–S58. Doi: http://dx.doi.org//10.1093/geronb/52B.1.S49.10.1093/geronb/52B.1.S499008681Open DOISearch in Google Scholar

Understanding Society. 2016. “Understanding Society: Innovation Panel, Waves 1–7, 2008–2014 [data collection]. 6th edition [Computer software manual]. UK Data Service. Doi: 10.5255/UKDA-SN-6849-7.10.5255/UKDA-SN-6849-7Open DOISearch in Google Scholar

University of London. Institute of Education. Centre for Longitudinal Studies, Millennium Cohort Study: First Survey, 2001–2003 [computer file]. 6th edition. Colchester, Essex: UK Data Archive [distributor], SN: 4683. (2007, March). Available at: http://dx.doi.org/10.5255/UKDA-SN-4683-1.10.5255/UKDA-SN-4683-1Open DOISearch in Google Scholar

Van der Palm, D.W., L.A. Van der Ark, and J.K. Vermunt. 2016. “Divisive Latent Class Modeling as a Density Estimation Method for Categorical Data.” Journal of Classification 1–21. Doi: http://dx.doi.org/10.1007/s00357-016-9195-5.10.1007/s00357-016-9195-5Open DOISearch in Google Scholar

Van der Vaart, W. and T. Glasner. 2007. “Applying a Timeline as a Recall Aid in a Telephone Survey: a Record Check Study.” Applied Cognitive Psychology 21: 227–238. Doi: http://dx.doi.org/10.1002/acp.1338.10.1002/acp.1338Open DOISearch in Google Scholar

Vermunt, J.K. and J. Magidson. 2004. “Latent Class Analysis.” The Sage Encyclopedia of Social Sciences Research Methods 549–553. Available at: http://members.home.nl/jeroenvermunt/ermss2004a.pdf (accessed April 25, 2017).Search in Google Scholar

Vermunt, J.K. and J. Magidson. 2013a. Latent GOLD 5.0 Up-grade Manual [Computer software manual]. Belmont, MA. Available at: https://www.statisticalinnovations.com/wp-content/uploads/LG5manual.pdf (accessed April 25, 2017).Search in Google Scholar

Vermunt, J.K. and J. Magidson. 2013b. “Technical Guide for Latent GOLD 5.0: Basic, Advanced, and Syntax.” Statistical Innovations Inc., Belmont, MA. Available at: https://www.statisticalinnovations.com/wp-content/uploads/LGtecnical.pdf (accessed April 25, 2017).Search in Google Scholar

Vermunt, J.K., J.R. Van Ginkel, L.A. Van Der Ark, and K. Sijtsma. 2008. “Multiple Imputation of Incomplete Categorical Data Using Latent Class Analysis.” Sociological Methodology 38: 369–397. Doi: http://dx.doi.org/10.1111/j.1467-9531.2008.00202.x.10.1111/j.1467-9531.2008.00202.xOpen DOISearch in Google Scholar

Vink, G. and S. van Buuren. 2014. “Pooling Multiple Imputations When the sample Happens to be the Population.” arXiv preprint arXiv:1409.8542. Available at: https://arxiv.org/abs/1409.8542.Search in Google Scholar

Zhang, L.-C. 2012. “Topics of Statistical Theory for Register-Based Statistics and Data Integration.” Statistica Neerlandica 66: 41–63. Available at: http://dx.doi.org/10.1111/j.1467-9574.2011.00508.x.10.1111/j.1467-9574.2011.00508.xOpen DOISearch in Google Scholar

Zhang, L.-C. and J. Pannekoek. 2015. “Optimal Adjustments for Inconsistency in Imputed Data.” Survey Methodology 41: 127–144. Available at: http://www.statcan.gc.ca/pub/12-001-x/12-001-x2015001-eng.pdf (accessed April 25, 2017).Search in Google Scholar

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