Professor Jörg Drechsler

ongoing Projects

• Synthetic data in statistics and computer science - a systematic evaluation and methodological improvements
• High frequency person panel: Development study
• Towards an End-to-End Approach to Formal Privacy for Sample Surveys

finished Projects

• Überarbeitung des IAB-Publikationsratings
• Enhancing the Quality and Utility of Longitudinal Data for Education Research
• Imputation and record linkage strategies for educational data collected from surveys and administrative sources
• Imputation of right-censored wages in the BeH
• Synthetic datasets for the geocoded IEB
• Imputation der Arbeitszeitinformationen in der BeH
• Imputation der Bildungsvariable in der IEB
• Entwurf eines Publikationsratings für das IAB
• Imputation und Gewichtung zum Umgang mit fehlenden Werten in hierarchischen Längsschnitterhebungen
• Generating synthetic datasets for the BHP
• Blue ETS - BLUE-Enterprise and Trade Statistics
• Verbesserung der informationellen Infrastruktur für das E-Science Age (infinitE)
• Wirtschaftsstatistische Paneldaten und faktische Anonymisierung (FAWE)
• Prüfung der Möglichkeiten der tieferen Regional- und Berufsgliederung sowie der multiplen Datenimputation der Quartalsdaten der Erhebung des gesamtwirtschaftlichen Stellenangebots 2005/2006
• Fragebogensplit Offene-Stellen Erhebung

• Re-identification potential of structured health data

  Drechsler, J. & Pauly, H. (2024): Das Reidentifikationspotenzial von strukturierten Gesundheitsdaten. In: Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz, Vol. 67, p. 164-170. DOI:10.1007/s00103-023-03820-2

• An overview of data protection strategies for individual-level geocoded data

  Steffen, M., Körner, K. & Drechsler, J. (2023): An overview of data protection strategies for individual-level geocoded data. In: United Nations Economic Commission for Europe (Hrsg.) (2023): UNECE Expert meeting on Statistical Data Confidentiality 2023, p. 1-13.

• Imputation der rechtszensierten Tagesentgelte für die BeH

  Drechsler, J., Ludsteck, J. & Moczall, A. (2023): Imputation der rechtszensierten Tagesentgelte für die BeH. (FDZ-Methodenreport 05/2023 (de)), Nürnberg, 25 p. DOI:10.5164/IAB.FDZM.2305.de.v1

• Differential Privacy for Government Agencies - Are We There Yet?

  Drechsler, J. (2023): Differential Privacy for Government Agencies - Are We There Yet? In: Journal of the American Statistical Association, Vol. 118, No. 541, p. 761-773. DOI:10.1080/01621459.2022.2161385

• Challenges in Measuring Utility for Fully Synthetic Data

  Drechsler, J. (2022): Challenges in Measuring Utility for Fully Synthetic Data. In: J. Domingo-Ferrer & M. Laurent (Hrsg.) (2022): Privacy in Statistical Databases 2022, p. 220-233. DOI:10.1007/978-3-031-13945-1_16

• Controlling Privacy Loss in Sampling Schemes: An Analysis of Stratified and Cluster Sampling

  Bun, M., Drechsler, J., Gaboardi, M., McMillan, A. & Sarathy, J. (2022): Controlling Privacy Loss in Sampling Schemes: An Analysis of Stratified and Cluster Sampling. In: L. Elisa Celis (Ed.) (2022): 3rd annual Symposium on Foundations of Responsible Computing (FORC), p. 1-24. DOI:10.4230/LIPIcs.FORC.2022.1

• Nonparametric Differentially Private Confidence Intervals for the Median

  Drechsler, J., Globus-Harris, I., McMillan, A., Sarathy, J. & Smith, A. (2022): Nonparametric Differentially Private Confidence Intervals for the Median. In: Journal of survey statistics and methodology, Vol. 10, No. 3, p. 804-829. DOI:10.1093/jssam/smac021

• Accuracy Gains from Privacy Amplification Through Sampling for Differential Privacy

  Hu, J., Drechsler, J. & Kim, H. (2022): Accuracy Gains from Privacy Amplification Through Sampling for Differential Privacy. In: Journal of survey statistics and methodology, Vol. 10, No. 3, p. 688-719. DOI:10.1093/jssam/smac012

• Herausforderungen bei der Anonymisierung - von der Pseudonymisierung über synthetische Daten zum Konzept der Differential Privacy

  Drechsler, J. (2022): Herausforderungen bei der Anonymisierung - von der Pseudonymisierung über synthetische Daten zum Konzept der Differential Privacy. In: J. Baas (Hrsg.) (2022): Gesundheit im Zeitalter der Plattformökonomie, p. 80-88.

• Accounting for longitudinal data structures when disseminating synthetic data to the public

  Rashid, S., Drechsler, J. & Mitra, R. (2021): Accounting for longitudinal data structures when disseminating synthetic data to the public. In: United Nations Economic Comission for Europe (Hrsg.) (2021): Expert Meeting on Statistical Data Confidentiality, Genf, p. 1-12.

• Synthesizing Geocodes to Facilitate Access to Detailed Geographical Information in Large-Scale Administrative Data

  Drechsler, J. & Hu, J. (2021): Synthesizing Geocodes to Facilitate Access to Detailed Geographical Information in Large-Scale Administrative Data. In: Journal of survey statistics and methodology, Vol. 9, No. 3, p. 523-548., accepted on August 21, 2020. DOI:10.1093/jssam/smaa035

• Synthetic microdata for establishment surveys under informative sampling

  Kim, H., Drechsler, J. & Thompson, K. (2021): Synthetic microdata for establishment surveys under informative sampling. In: Journal of the Royal Statistical Society. Series A, Statistics in Society, Vol. 184, No. 1, p. 255-281. DOI:10.1111/rssa.12622

• The R Package hmi: A Convenient Tool for Hierarchical Multiple Imputation and Beyond

  Speidel, M., Drechsler, J. & Jolani, S. (2020): The R Package hmi: A Convenient Tool for Hierarchical Multiple Imputation and Beyond. In: Journal of statistical software, Vol. 95, No. 9, p. 1-48. DOI:10.18637/jss.v095.i09

• TippingSens: An R Shiny Application to Facilitate Sensitivity Analysis for Causal Inference Under Confounding

  Haensch, A., Drechsler, J. & Bernhard, S. (2020): TippingSens: An R Shiny Application to Facilitate Sensitivity Analysis for Causal Inference Under Confounding. (IAB-Discussion Paper 29/2020), Nürnberg, 39 p.

• Secure Matrix Computation: A Viable Alternative to Record Linkage?

  Drechsler, J. & Klein, B. (2020): Secure Matrix Computation: A Viable Alternative to Record Linkage? In: J. Domingo-Ferrer & K. Muralidhar (Hrsg.) (2020): Privacy in Statistical Databases, Cham, p. 240-254. DOI:10.1007/978-3-030-57521-2_17

• Applying data synthesis for longitudinal business data across three countries

  Alam, M., Dostie, B., Drechsler, J. & Vilhuber, L. (2020): Applying data synthesis for longitudinal business data across three countries. In: Statistics in transition, Vol. 21, No. 4, p. 212-236. DOI:10.21307/stattrans-2020-039

• Multiple Imputation

  Drechsler, J. (2020): Multiple Imputation. In: P. Atkinson, S. Delamont, A. Cernat, J. W. Sakshaug & R. A. Williams (Hrsg.) (2020), SAGE Research methods foundations: an encyclopedia, o. Sz. DOI:10.4135/9781526421036885886

• In memory of Professor Susanne Rässler

  Drechsler, J., Kiesl, H., Meinfelder, F., Raghunathan, T., Rubin, D., Schenker, N. & Zell, E. (2019): In memory of Professor Susanne Rässler. In: Journal of official statistics, Vol. 35, No. 1, p. 285-286. DOI:10.2478/jos-2019-0013

• Statistical matching as a supplement to record linkage

  Gessendorfer, J., Beste, J., Drechsler, J. & Sakshaug, J. (2018): Statistical matching as a supplement to record linkage. A valuable method to tackle nonconsent bias? In: Journal of official statistics, Vol. 34, No. 4, p. 909-933., accepted on June 20, 2018. DOI:10.2478/jos-2018-0045

• Some clarifications regarding fully synthetic data

  Drechsler, J. (2018): Some clarifications regarding fully synthetic data. In: J. Domingo-Ferrer & F. Montes (Hrsg.) (2018): Privacy in statistical databases : UNESCO Chair in Data Privacy International Conference, PSD 2018 Valencia, Spain, September 26 - 28, 2018 Proceedings (Lecture Notes in Computer Science, 11126), p. 109-121. DOI:10.1007/978-3-319-99771-1_8

• R package hmi: a convenient tool for hierarchical multiple imputation and beyond

  Speidel, M., Drechsler, J. & Jolani, S. (2018): R package hmi: a convenient tool for hierarchical multiple imputation and beyond. (IAB-Discussion Paper 16/2018), Nürnberg, 55 p.

• Preface to the papers on 'Data confidentiality and statistical disclosure control'

  Drechsler, J. & Shlomo, N. (2019): Preface to the papers on 'Data confidentiality and statistical disclosure control'. In: Journal of the Royal Statistical Society. Series A, Statistics in Society, Vol. 181, No. 3, p. 607-608. DOI:10.1111/rssa.12383

• Synthetische Daten

  Drechsler, J. & Jentzsch, N. (2018): Synthetische Daten. Innovationspotential und gesellschaftliche Herausforderungen. Berlin, 26 p.

• Biases in multilevel analyses caused by cluster-specific fixed-effects imputation

  Speidel, M., Drechsler, J. & Sakshaug, J. (2018): Biases in multilevel analyses caused by cluster-specific fixed-effects imputation. In: Behavior research methods, Vol. 50, No. 5, p. 1824-1840. DOI:10.3758/s13428-017-0951-1

• Discussion of the synthetic data papers published in the previous issue

  Drechsler, J. (2016): Discussion of the synthetic data papers published in the previous issue. In: Statistical Journal of the IAOS, Vol. 32, No. 2, p. 271-274. DOI:10.3233/SJI-161001

• Beat the heap: An imputation strategy for valid inferences from rounded income data

  Drechsler, J. & Kiesl, H. (2016): Beat the heap: An imputation strategy for valid inferences from rounded income data. In: Journal of Survey Statistics and Methodology, Vol. 4, No. 1, p. 22-42. DOI:10.1093/jssam/smv032

• MI double feature: Multiple imputation to address nonresponse and rounding errors in income questions

  Drechsler, J., Kiesl, H. & Speidel, M. (2015): MI double feature: Multiple imputation to address nonresponse and rounding errors in income questions. In: Austrian Journal of Statistics, Vol. 44, No. 2, p. 59-71. DOI:10.17713/ajs.v44i2.77

• Generating synthetic geocoding information for public release

  Hu, J. & Drechsler, J. (2015): Generating synthetic geocoding information for public release. In: S. A. Europäische Kommission (Hrsg.) (2015): NTTS - Conferences on New Techniques and Technologies for Statistics. Brussels, 9-13 March 2015. Proceedings, p. 56-59.

• Multiple imputation of multilevel missing data rigor vs. simplicity

  Drechsler, J. (2015): Multiple imputation of multilevel missing data rigor vs. simplicity. In: Journal of educational and behavioral statistics, Vol. 40, No. 1, p. 69-95. DOI:10.3102/1076998614563393

• Synthetic longitudinal business databases for international comparisons

  Drechsler, J. & Vilhuber, L. (2014): Synthetic longitudinal business databases for international comparisons. In: J. Domingo-Ferrer (Hrsg.) (2014): Privacy in statistical databases 2014 : UNESCO Chair in Data Privacy, International Conference, PSD 2014, Ibiza, Spain, September 17-19, 2014. Proceedings (Lecture notes in computer science, 8744), p. 243-252. DOI:10.1007/978-3-319-11257-2_19

• A first step towards a German SynLBD

  Drechsler, J. & Vilhuber, L. (2014): A first step towards a German SynLBD. Constructing a German longitudinal business database. In: Statistical Journal of the IAOS, Vol. 30, No. 2, p. 137-142. DOI:10.3233/SJI-140812

• Disclosure risk from factor scores

  Bleninger, P., Drechsler, J. & Ronning, G. (2014): Disclosure risk from factor scores. In: Journal of official statistics, Vol. 30, No. 1, p. 107-122. DOI:10.2478/jos-2014-0006

• Beat the heap - an imputation strategy for valid inferences from rounded income data

  Drechsler, J. & Kiesl, H. (2014): Beat the heap - an imputation strategy for valid inferences from rounded income data. (IAB-Discussion Paper 02/2014), Nürnberg, 26 p.

• Evaluating the potential of differential privacy mechanisms for census data

  Soria-Comas, J. & Drechsler, J. (2013): Evaluating the potential of differential privacy mechanisms for census data. (UNECE Working paper), New York, 12 p.

• Replicating the synthetic LBD with German establishment data

  Vilhuber, L. & Drechsler, J. (2013): Replicating the synthetic LBD with German establishment data. (Labor Dynamics Institute. Working Paper), 6 p.

• Generating useful test data for complex linked employer-employee datasets

  Dorner, M., Drechsler, J. & Jacobebbinghaus, P. (2012): Generating useful test data for complex linked employer-employee datasets. In: J. Domingo-Ferrer & I. Tinnirello (Hrsg.) (2012): Privacy in statistical databases (Lecture notes in computer science, 7556), p. 165-178.

• Combining synthetic data with subsampling to create public use microdata files for large scale surveys

  Drechsler, J. & Reiter, J. (2012): Combining synthetic data with subsampling to create public use microdata files for large scale surveys. In: Survey Methodology, Vol. 38, No. 1, p. 73-79.

• Remote Access

  Ronning, G., Bleninger, P., Drechsler, J. & Gürke, C. (2011): Remote Access. Eine Welt ohne Mikrodaten?? (FDZ-Arbeitspapier 33), Wiesbaden, 59 p.

• An empirical evaluation of easily implemented, nonparametric methods for generating synthetic datasets

  Drechsler, J. & Reiter, J. (2011): An empirical evaluation of easily implemented, nonparametric methods for generating synthetic datasets. In: Europäische Kommission (Hrsg.) (2011): Proceedings of the Eurostat Conference on New Techniques and Technologies for Statistics (NTTS) 2011, Brussels, p. 1-12.

• An empirical evaluation of easily implemented, nonparametric methods for generating synthetic datasets

  Drechsler, J. & Reiter, J. (2011): An empirical evaluation of easily implemented, nonparametric methods for generating synthetic datasets. In: Computational Statistics and Data Analysis, Vol. 55, No. 12, p. 3232-3243. DOI:10.1016/j.csda.2011.06.006

• Disclosure risk from factor scores in a remote access environment

  Bleninger, P., Drechsler, J. & Ronning, G. (2011): Disclosure risk from factor scores in a remote access environment. (Joint UNECE/Eurostat work session on statistical data confidentiality 2011. Working paper 02), New York, 14 p.

• Improved variance estimation for fully synthetic datasets

  Drechsler, J. (2011): Improved variance estimation for fully synthetic datasets. (Joint UNECE/Eurostat work session on statistical data confidentiality 2011. Working paper 18), New York, 13 p.

• Remote data access and the risk of disclosure from linear regression

  Bleninger, P., Drechsler, J. & Ronning, G. (2011): Remote data access and the risk of disclosure from linear regression. In: Statistics and operations research transactions (SORT) No. Special Issue, p. 7-24.

• New data dissemination approaches in old Europe

  Drechsler, J. (2012): New data dissemination approaches in old Europe. Synthetic datasets for a German establishment survey. In: Journal of applied statistics, Vol. 39, No. 2, p. 243-265. DOI:10.1080/02664763.2011.584523

• Generating multiply imputed synthetic datasets : theory and implementation. Gerhard-Fürst-Award

  Drechsler, J. (2011): Erzeugung synthetischer Datensätze durch multiple Imputation. Theorie und Implementierung in der Praxis. Gerhard-Fürst-Preis. In: Wirtschaft und Statistik No. 4, p. 402-407.

• Methodenreport: Synthetische Scientific-Use-Files der Welle 2007 des IAB-Betriebspanels

  Drechsler, J. (2011): Methodenreport: Synthetische Scientific-Use-Files der Welle 2007 des IAB-Betriebspanels. (FDZ-Methodenreport 01/2011 (de)), Nürnberg, 19 p.

• Using support vector machines for generating synthetic datasets

  Drechsler, J. (2011): Using support vector machines for generating synthetic datasets. In: J. Domingo-Ferrer & E. Magkos (Hrsg.) (2011): Privacy in statistical databases : UNESCO Chair in Data Privacy, International Conference, PSD 2010, Corfu, Greece, September 22-24, 2010. Proceedings (Lecture notes in computer science, 6344), p. 148-161. DOI:10.1007/978-3-642-15838-4

• Remote data access and the risk of disclosure from linear regression

  Bleninger, P., Drechsler, J. & Ronning, G. (2011): Remote data access and the risk of disclosure from linear regression. An empirical study. In: J. Domingo-Ferrer & E. Magkos (Hrsg.) (2011): Privacy in statistical databases : UNESCO Chair in Data Privacy, International Conference, PSD 2010, Corfu, Greece, September 22-24, 2010. Proceedings (Lecture notes in computer science, 6344), p. 220-233. DOI:10.1007/978-3-642-15838-4_20

• Multiple imputation of missing values in the wave 2007 of the IAB Establishment Panel

  Drechsler, J. (2010): Multiple imputation of missing values in the wave 2007 of the IAB Establishment Panel. (IAB-Discussion Paper 06/2010), Nürnberg, 29 p.

• Releasing multiply-imputed synthetic data generated in two stages to protect confidentiality

  Reiter, J. & Drechsler, J. (2010): Releasing multiply-imputed synthetic data generated in two stages to protect confidentiality. In: Statistica Sinica, Vol. 20, No. 1, p. 405-421.

• Remote Access

  Ronning, G., Bleninger, P., Drechsler, J. & Gürke, C. (2010): Remote Access. Eine Welt ohne Mikrodaten?? (IAW-Diskussionspapiere 66), Tübingen, 64 p.

• Multiple imputation in practice

  Drechsler, J. (2011): Multiple imputation in practice. A case study using a complex German establishment survey. In: Advances in statistical analysis, Vol. 95, No. 1, p. 1-26. DOI:10.1007/s10182-010-0136-z

• Sampling with synthesis

  Drechsler, J. & Reiter, J. (2010): Sampling with synthesis. A new approach for releasing public use census microdata. In: Journal of the American Statistical Association, Vol. 105, No. 492, p. 1347-1357. DOI:10.1198/jasa.2010.ap09480

• Synthetic datasets for the German IAB Establishment Panel

  Drechsler, J. (2009): Synthetic datasets for the German IAB Establishment Panel. (Joint UNECE/Eurostat Work Session on Statistical Data Confidentiality 2009. Working paper 10), New York, 13 p.

• Disclosure control in business data

  Drechsler, J. (2009): Disclosure control in business data. Experiences with multiply imputed synthetic datasets for the German IAB Establishment Survey. In: Europäische Kommission (Hrsg.) (2009): Proceedings of the Eurostat Conference on New Techniques and Technologies for Statistics (NTTS), 2009, Brussels, p. 1-10.

• ESSNET-SDC deliverable report on synthetic data files

  Domingo-Ferrer, J., Drechsler, J. & Polettini, S. (2009): ESSNET-SDC deliverable report on synthetic data files. The Hague, 32 p.

• Far from normal: Multiple imputation of missing values in a German establishment survey

  Drechsler, J. (2009): Far from normal: Multiple imputation of missing values in a German establishment survey. (United Nations, Economic Commission for Europe. Working paper 21), New York, 13 p.

• Disclosure risk and data utility for partially synthetic data

  Drechsler, J. & Reiter, J. (2009): Disclosure risk and data utility for partially synthetic data. An empirical study using the German IAB Establishment Survey. In: Journal of official statistics, Vol. 25, No. 4, p. 589-603.

• Accounting for intruder uncertainty due to sampling when estimating identification disclosure risks in partially synthetic data

  Drechsler, J. & Reiter, J. (2008): Accounting for intruder uncertainty due to sampling when estimating identification disclosure risks in partially synthetic data. In: J. Domingo-Ferrer & Y. Saygin (Hrsg.) (2008): Privacy in statistical databases : UNESCO Chair in Data Privacy International Conference, PSD 2008, Istanbul, Turkey, September 24-26, 2008. Proceedings (Lecture notes in computer science, 5262), p. 227-238.

• Estimation of vacancies by NACE and ISCO at disaggregated regional level

  Kettner, A., Drechsler, J., Rebien, M., Schmidt, K., Smerdjieva, M., Stops, M. & Vogler-Ludwig, K. (2007): Estimation of vacancies by NACE and ISCO at disaggregated regional level. (IAB-Bibliothek 310), Nürnberg, 197 p.

• Evaluating different approaches for multiple imputation under linear constraints

  Drechsler, J. & Raghunathan, T. (2008): Evaluating different approaches for multiple imputation under linear constraints. (United Nations, Economic Commission for Europe. Working paper 25), New York, 12 p.

• Comparing fully and partially synthetic datasets for statistical disclosure control in the German IAB Establishment Panel

  Drechsler, J., Bender, S. & Rässler, S. (2008): Comparing fully and partially synthetic datasets for statistical disclosure control in the German IAB Establishment Panel. In: Transactions on Data Privacy, Vol. 1, No. 3, p. 105-130.

• Does convergence really matter?

  Drechsler, J. & Rässler, S. (2008): Does convergence really matter? In: Shalabh & C. Heumann (Hrsg.) (2008): Recent advances in linear models and related areas : essays in honour of Helge Toutenburg (Statistical theory and methods, 15).

• A new approach for disclosure control in the IAB Establishment Panel

  Drechsler, J., Dundler, A., Bender, S., Rässler, S. & Zwick, T. (2008): A new approach for disclosure control in the IAB Establishment Panel. Multiple imputation for a better data access. In: Advances in statistical analysis, Vol. 92, No. 4, p. 439-458. DOI:10.1007/s10182-008-0090-1

• A new approach for disclosure control in the IAB Establishment Panel

  Drechsler, J., Dundler, A., Bender, S., Rässler, S. & Zwick, T. (2007): A new approach for disclosure control in the IAB Establishment Panel. Multiple imputation for a better data access. (IAB-Discussion Paper 11/2007), Nürnberg, 31 p.

• Comparing fully and partially synthetic data sets for statistical disclosure control in the German IAB Establishment Panel

  Drechsler, J., Bender, S. & Rässler, S. (2007): Comparing fully and partially synthetic data sets for statistical disclosure control in the German IAB Establishment Panel. (United Nations, Economic Commission for Europe. Working paper 11), New York, 8 p.

• Releasing multiply-imputed synthetic data generated in two stages to protect confidentiality

  Reiter, J. & Drechsler, J. (2007): Releasing multiply-imputed synthetic data generated in two stages to protect confidentiality. (IAB-Discussion Paper 20/2007), Nürnberg, 26 p.

• A new approach for disclosure control in the IAB Establishment Panel

  Bender, S., Drechsler, J., Dundler, A., Rässler, S. & Zwick, T. (2006): A new approach for disclosure control in the IAB Establishment Panel. Multiple imputation for a better data access. (United Nations, Economic Commission for Europe. Working paper 18), New York, 18 p.

• Estimation of vacancies by NACE and ISCO on disaggregated regional level

  Kettner, A., Drechsler, J., Rebien, M., Schmidt, K., Semerdjiva, M., Stops, M. & Vogler-Ludwig, K. (2006): Estimation of vacancies by NACE and ISCO on disaggregated regional level. Nürnberg, 101 p., Anhang.

• A new approach for disclosure control in the IAB Establishment Panel

  Drechsler, J., Dundler, A. & Rässler, S. (2006): A new approach for disclosure control in the IAB Establishment Panel. Multiple imputation for a better data access. In: (2006): Proceedings of privacy in statistical data bases.

• 30 Years of Synthetic Data (im Erscheinen)

  Drechsler, J. & Haensch, A. (2024): 30 Years of Synthetic Data (im Erscheinen). In: Statistical Science, accepted on February 01, 2024.