Publications: Statistical Methods (KEM)
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FDI and onshore task composition: evidence from German firms with affiliates in the Czech Republic
Körner, K. & Le Moigne, M. (2023): FDI and onshore task composition: evidence from German firms with affiliates in the Czech Republic. In: Journal for labour market research, Vol. 57. DOI:10.1186/s12651-023-00346-7
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The IAB-SMART-Mobility Module: An Innovative Research Dataset with Mobility Indicators Based on Raw Geodata
Zimmermann, F., Filser, A., Haas, G. & Bähr, S. (2024): The IAB-SMART-Mobility Module: An Innovative Research Dataset with Mobility Indicators Based on Raw Geodata. In: Jahrbücher für Nationalökonomie und Statistik, Vol. 244, No. 5-6, p. 685-698. DOI:10.1515/jbnst-2023-0051
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How to improve the substantive interpretation of regression results when the dependent variable is logged
Rittmann, O., Neunhoeffer, M. & Gschwend, T. (2025): How to improve the substantive interpretation of regression results when the dependent variable is logged. In: Political Science Research and Methods, Vol. 13, No. 1, p. 203-211. DOI:10.1017/psrm.2023.29
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Nonresponse trends in establishment panel surveys: findings from the 2001–2017 IAB establishment panel
König, C. & Sakshaug, J. (2023): Nonresponse trends in establishment panel surveys: findings from the 2001–2017 IAB establishment panel. In: Journal for labour market research, Vol. 57. DOI:10.1186/s12651-023-00349-4
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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
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To Link or Synthesize? An Approach to Data Quality Comparison
Smith, D., Elliot, M. & Sakshaug, J. (2023): To Link or Synthesize? An Approach to Data Quality Comparison. In: Journal of Data and Information Quality, Vol. 15, No. 2, p. 1-20. DOI:10.1145/3580487
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Ethical Considerations for Augmenting Surveys with Auxiliary Data Sources
Struminskaya, B. & Sakshaug, J. (2023): Ethical Considerations for Augmenting Surveys with Auxiliary Data Sources. In: Public opinion quarterly, Vol. 87, No. S1, p. 619-633. DOI:10.1093/poq/nfad030
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Augmenting Surveys with Paradata, Administrative Data, and Contextual Data
Sakshaug, J. & Struminskaya, B. (2023): Augmenting Surveys with Paradata, Administrative Data, and Contextual Data. In: Public opinion quarterly, Vol. 87, No. S1, p. 475-479. DOI:10.1093/poq/nfad026
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Tracking country innovation performance: The Innovation Output Indicator 2022
Bello, M., Caperna, G., Damioli, G., Smallenbroek, O. & Steffen, M. (2023): Tracking country innovation performance: The Innovation Output Indicator 2022. (JRC technical report), Luxemburg: Publications Office of the European Union, 55 p. DOI:10.2760/346938
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Recent Advances in Data Integration
Sakshaug, J. & Steorts, R. (2023): Recent Advances in Data Integration. In: Journal of survey statistics and methodology, Vol. 11, No. 3, p. 513-517. DOI:10.1093/jssam/smad009
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Regional Labour Market Forecasts March 2024
Heining, J., Jahn, D., Körner, K., Rossen, A., Teichert, C. & Weyh, A. (2024): Regional Labour Market Forecasts March 2024. Current Data and Indicators. (Institut für Arbeitsmarkt- und Berufsforschung. Aktuelle Daten und Indikatoren 01/2024 (en)), Nürnberg, 22 p. DOI:10.48720/IAB.RA.241.en
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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
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Studie zu Betrieben in der Covid-19-Krise (BeCovid)
Bellmann, L., Gensicke, M., Gleiser, P., Hartmann, J., Hensgen, S., Kagerl, C., Koch, T., König, C., Kleifgen, E., Künzel, S., Leber, U., Moritz, M., Pohlan, L., Riedmann, A., Roth, D., Schierholz, M., Stegmaier, J., Strauß, A., Tschersich, N. & Umkehrer, M. (2023): Studie zu Betrieben in der Covid-19-Krise (BeCovid). (FDZ-Methodenreport 02/2023 (de)), Nürnberg, 67 p. DOI:10.5164/IAB.FDZM.2302.de.v1
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Transitioning an employee panel survey from telephone to online and mixed-mode data collection
Mackeben, J. & Sakshaug, J. (2023): Transitioning an employee panel survey from telephone to online and mixed-mode data collection. In: Statistical Journal of the IAOS, Vol. 39, No. 1, p. 213-232. DOI:10.3233/SJI-220088
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Why using Google's reCAPTCHA to protect your survey against bots is a bad idea
Haas, G. (2023): Why using Google's reCAPTCHA to protect your survey against bots is a bad idea. In: Medium : Human Stories & Ideas No. 01.03.2023.
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River Sampling – a Fishing Expedition: A Non-Probability Case Study
Murray-Watters, A., Zins, S., Silber, H., Gummer, T. & Lechner, C. (2023): River Sampling – a Fishing Expedition: A Non-Probability Case Study. In: Methods, Data, Analyses, Vol. 17, No. 1, p. 3-28. DOI:10.12758/mda.2022.05
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Advances in Business Statistics, Methods and Data Collection
Snijkers, G., Bavdaž, M., Bender, S., Jones, J., MacFeely, S., Sakshaug, J., Thompson, K. & Delden, A. (eds.) (2023): Advances in Business Statistics, Methods and Data Collection. Chichester: Wiley, 856 p.
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Recent Findings from Experiments in Establishment Surveys
Langeland, J., Ridolfo, H., McCarthy, J., Ott, K., Kilburg, D., CyBulski, K., Krakowiecki, M., Vittoriano, L., Potts, M., Küfner, B., Sakshaug, J. & Zins, S. (2023): Recent Findings from Experiments in Establishment Surveys. In: G. Snijkers, M. Bavdaž, S. Bender, S. MacFeely, J. Sakshaug, K. J. Thompson & A. v. Delden (Hrsg.) (2023): Advances in Business Statistics, Methods and Data Collection, p. 437-467. DOI:10.1002/9781119672333.ch19
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Effects of mixing modes on nonresponse and measurement error in an economic panel survey
Sakshaug, J., Beste, J. & Trappmann, M. (2023): Effects of mixing modes on nonresponse and measurement error in an economic panel survey. In: Journal for labour market research, Vol. 57. DOI:10.1186/s12651-022-00328-1
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Detecting Interviewer Fraud Using Multilevel Models
Olbrich, L., Kosyakova, Y., Sakshaug, J. & Schwanhäuser, S. (2024): Detecting Interviewer Fraud Using Multilevel Models. In: Journal of survey statistics and methodology, Vol. 12, No. 1, p. 14-35. DOI:10.1093/jssam/smac036