Publikationen: Kompetenzzentrum Empirische Methoden (KEM)
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Nonprobability sampling and causal analysis
Kohler, Ulrich, Frauke Kreuter & Elizabeth A. Stuart (2019): Nonprobability sampling and causal analysis. In: Annual review of statistics and its application, Jg. 6, S. 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, Brady T., Joseph Sakshaug & Guy Alain S. Aurelien (2018): Accounting for complex sampling in survey estimation: A review of current software tools. In: Journal of official statistics, Jg. 34, H. 3, S. 721-752. DOI:10.2478/jos-2018-0034
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Some clarifications regarding fully synthetic data
Drechsler, Jörg (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), S. 109-121. DOI:10.1007/978-3-319-99771-1_8
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Do we measure employment durations correctly?
Jaenichen, Ursula (2018): Do we measure employment durations correctly? The case of German administrative employment data. (FDZ-Methodenreport 10/2018 (en)), Nürnberg, 25 S. 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, Ulrich, Johannes Ludsteck & Alexandra Schmucker (2018): Skilled or unskilled - Improving the information on qualification for employee data in the IAB Employee Biography. (FDZ-Methodenreport 09/2018 (en)), Nürnberg, 22 S. 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, Matthias, Jörg Drechsler & Shahab Jolani (2018): R package hmi: a convenient tool for hierarchical multiple imputation and beyond. (IAB-Discussion Paper 16/2018), Nürnberg, 55 S.
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Preface to the papers on 'Data confidentiality and statistical disclosure control'
Drechsler, Jörg & Natalie Shlomo (2019): Preface to the papers on 'Data confidentiality and statistical disclosure control'. In: Journal of the Royal Statistical Society. Series A, Statistics in Society, Jg. 181, H. 3, S. 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, Joseph & Manfred Antoni (2019): Evaluating the utility of indirectly linked federal administrative records for nonresponse bias adjustment. In: Journal of Survey Statistics and Methodology, Jg. 7, H. 2, S. 227-249. DOI:10.1093/jssam/smy009
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The impact of interviewer effects on regression coefficients
Fischer, Micha, Brady T. West & Michael R. Elliott (2019): The impact of interviewer effects on regression coefficients. In: Journal of Survey Statistics and Methodology, Jg. 7, H. 2, S. 250-274. DOI:10.1093/jssam/smy007
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Eine Hilfsklassifikation mit Tätigkeitsbeschreibungen für Zwecke der Berufskodierung
Schierholz, Malte, Lorraine Brenner, Lea Cohausz, Lisa Damminger, Lisa Fast, Ann-Kathrin Hörig, Anna-Lena Huber, Theresa Ludwig, Annabell Petry & Laura Tschischka (2018): Eine Hilfsklassifikation mit Tätigkeitsbeschreibungen für Zwecke der Berufskodierung. Leitgedanken und Dokumentation. (IAB-Discussion Paper 13/2018), Nürnberg, 43 S.
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Synthetische Daten
Drechsler, Jörg & Nicola Jentzsch (2018): Synthetische Daten. Innovationspotential und gesellschaftliche Herausforderungen. Berlin, 26 S.
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Participating in a panel survey
Bach, Ruben L. & Stephanie Eckmann (2018): Participating in a panel survey. Changes respondents' labour market behaviour. In: Journal of the Royal Statistical Society. Series A, Statistics in Society, Jg. 17, H. 3, S. 443-456. DOI:10.1111/rssa.12367
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Strategies for increasing the accuracy of interviewer observations of respondent features
West, Brady T. & Frauke Kreuter (2018): Strategies for increasing the accuracy of interviewer observations of respondent features. Evidence from the U.S. National Survey of Family Growth. In: Methodology, Jg. 14, H. 1, S. 16-29. DOI:10.1027/1614-2241/a000142
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Misreporting to looping questions in surveys
Eckman, Stephanie & Frauke Kreuter (2018): Misreporting to looping questions in surveys. Recall, motivation and burden. In: Survey research methods, Jg. 12, H. 1, S. 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, Brady T. & Joseph Sakshaug (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 H. Januar 2018, S. 1-10. DOI:10.13094/SMIF-2018-00001
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IAB-SMART-Studie: Mit dem Smartphone den Arbeitsmarkt erforschen
Bähr, Sebastian, Georg-Christoph Haas, Florian Keusch, Frauke Kreuter & Mark Trappmann (2018): IAB-SMART-Studie: Mit dem Smartphone den Arbeitsmarkt erforschen. In: IAB-Forum H. 09.01.2018, o. Sz.
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Learning from mouse movements: Improving questionnaire and respondents' user experience through passive data collection
Horwitz, Rachel, Sarah Brockhaus, Felix Henninger, Pascal Kieslich, Malte Schierholz, Florian Keusch & Frauke Kreuter (2017): Learning from mouse movements: Improving questionnaire and respondents' user experience through passive data collection. (IAB-Discussion Paper 34/2017), Nürnberg, 25 S.
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Challenge to the established curriculum
Gould, Robert, Roger D. Peng, Frauke Kreuter, Randall Pruim, Jeff Witmer & George W. Cobb (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 S. 415-432. DOI:10.1007/978-3-319-66195-7_13
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International program in survey and data science
Kreuter, Frauke, Florian Keusch, Evgenia Samoilova & Karin Frößinger (2018): International program in survey and data science. In: C. König, J. Schröder & E. Wiegand (Hrsg.) (2018): Big Data : Chancen, Risiken, Entwicklungstendenzen, S. 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, Martin & Frauke Kreuter (2017): Big Data - der Beginn eines goldenen Zeitalters für die Arbeitsmarktforschung? Ein Gespräch mit IAB-Forscherin Frauke Kreuter. In: IAB-Forum H. 17.11.2017, o. Sz.