Publications: Statistical Methods (KEM)
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Nonprobability sampling and causal analysis
Kohler, U., Kreuter, F. & Stuart, E. (2019): Nonprobability sampling and causal analysis. In: Annual review of statistics and its application, Vol. 6, p. 149-172. DOI:10.1146/annurev-statistics-030718-104951
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Accounting for complex sampling in survey estimation: A review of current software tools
West, B., Sakshaug, J. & Aurelien, G. (2018): Accounting for complex sampling in survey estimation: A review of current software tools. In: Journal of official statistics, Vol. 34, No. 3, p. 721-752. DOI:10.2478/jos-2018-0034
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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
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Do we measure employment durations correctly?
Jaenichen, U. (2018): Do we measure employment durations correctly? The case of German administrative employment data. (FDZ-Methodenreport 10/2018 (en)), Nürnberg, 25 p. DOI:10.5164/IAB.FDZM.1810.en.v1
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Skilled or unskilled - Improving the information on qualification for employee data in the IAB Employee Biography
Thomsen, U., Ludsteck, J. & Schmucker, A. (2018): Skilled or unskilled - Improving the information on qualification for employee data in the IAB Employee Biography. (FDZ-Methodenreport 09/2018 (en)), Nürnberg, 22 p. DOI:10.5164/IAB.FDZM.1809.en.v1
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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.
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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
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Evaluating the utility of indirectly linked federal administrative records for nonresponse bias adjustment
Sakshaug, J. & Antoni, M. (2019): Evaluating the utility of indirectly linked federal administrative records for nonresponse bias adjustment. In: Journal of Survey Statistics and Methodology, Vol. 7, No. 2, p. 227-249. DOI:10.1093/jssam/smy009
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The impact of interviewer effects on regression coefficients
Fischer, M., West, B. & Elliott, M. (2019): The impact of interviewer effects on regression coefficients. In: Journal of Survey Statistics and Methodology, Vol. 7, No. 2, p. 250-274. DOI:10.1093/jssam/smy007
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Eine Hilfsklassifikation mit Tätigkeitsbeschreibungen für Zwecke der Berufskodierung
Schierholz, M., Brenner, L., Cohausz, L., Damminger, L., Fast, L., Hörig, A., Huber, A., Ludwig, T., Petry, A. & Tschischka, L. (2018): Eine Hilfsklassifikation mit Tätigkeitsbeschreibungen für Zwecke der Berufskodierung. Leitgedanken und Dokumentation. (IAB-Discussion Paper 13/2018), Nürnberg, 43 p.
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Synthetische Daten
Drechsler, J. & Jentzsch, N. (2018): Synthetische Daten. Innovationspotential und gesellschaftliche Herausforderungen. Berlin, 26 p.
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Participating in a panel survey
Bach, R. & Eckmann, S. (2018): Participating in a panel survey. Changes respondents' labour market behaviour. In: Journal of the Royal Statistical Society. Series A, Statistics in Society, Vol. 17, No. 3, p. 443-456. DOI:10.1111/rssa.12367
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Strategies for increasing the accuracy of interviewer observations of respondent features
West, B. & Kreuter, F. (2018): Strategies for increasing the accuracy of interviewer observations of respondent features. Evidence from the U.S. National Survey of Family Growth. In: Methodology, Vol. 14, No. 1, p. 16-29. DOI:10.1027/1614-2241/a000142
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Misreporting to looping questions in surveys
Eckman, S. & Kreuter, F. (2018): Misreporting to looping questions in surveys. Recall, motivation and burden. In: Survey research methods, Vol. 12, No. 1, p. 59-74. DOI:10.18148/srm/2018.v12i1.7168
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The need to account for complex sampling features when analyzing establishment survey data: an illustration using the 2013 Business Research and Development Innovation Survey (BRDIS)
West, B. & Sakshaug, J. (2018): The need to account for complex sampling features when analyzing establishment survey data: an illustration using the 2013 Business Research and Development Innovation Survey (BRDIS). In: Survey Methods: Insights from the Field No. Januar 2018, p. 1-10. DOI:10.13094/SMIF-2018-00001
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IAB-SMART-Studie: Mit dem Smartphone den Arbeitsmarkt erforschen
Bähr, S., Haas, G., Keusch, F., Kreuter, F. & Trappmann, M. (2018): IAB-SMART-Studie: Mit dem Smartphone den Arbeitsmarkt erforschen. In: IAB-Forum No. 09.01.2018, o. Sz.
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Learning from mouse movements: Improving questionnaire and respondents' user experience through passive data collection
Horwitz, R., Brockhaus, S., Henninger, F., Kieslich, P., Schierholz, M., Keusch, F. & Kreuter, F. (2017): Learning from mouse movements: Improving questionnaire and respondents' user experience through passive data collection. (IAB-Discussion Paper 34/2017), Nürnberg, 25 p.
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Challenge to the established curriculum
Gould, R., Peng, R., Kreuter, F., Pruim, R., Witmer, J. & Cobb, G. (2018): Challenge to the established curriculum. A collection of reflections. In: D. Ben-Zvi, K. Makar & J. Garfield (Hrsg.) (2018): International handbook of research in statistics education, Cham, Springer London p. 415-432. DOI:10.1007/978-3-319-66195-7_13
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International programme in survey and data science
Kreuter, F., Keusch, F., Samoilova, E. & Frößinger, K. (2018): International program in survey and data science. In: C. König, J. Schröder & E. Wiegand (Hrsg.) (2018): Big Data : Chancen, Risiken, Entwicklungstendenzen, p. 27-41. DOI:10.1007/978-3-658-20083-1_4
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Big Data - der Beginn eines goldenen Zeitalters für die Arbeitsmarktforschung?
Schludi, M. & Kreuter, F. (2017): Big Data - der Beginn eines goldenen Zeitalters für die Arbeitsmarktforschung? Ein Gespräch mit IAB-Forscherin Frauke Kreuter. In: IAB-Forum No. 17.11.2017, o. Sz.