Publications: Statistical Methods (KEM)
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What are alternative data sources, and how to use them?
Kreuter, F. (2019): What are alternative data sources, and how to use them? In: The Survey statistician No. 79, p. 13-15.
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The impact of interviewer effects on skin color assessment in a cross-national context
Cernat, A., Sakshaug, J. & Castillo, J. (2019): The impact of interviewer effects on skin color assessment in a cross-national context. In: International Journal of Public Opinion Research, Vol. 31, No. 4, p. 779-793. DOI:10.1093/ijpor/edy030
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Do sequential mixed-mode surveys decrease nonresponse bias, measurement error bias, and total bias?
Sakshaug, J., Cernat, A. & Raghunathan, T. (2019): Do sequential mixed-mode surveys decrease nonresponse bias, measurement error bias, and total bias? An experimental study. In: Journal of survey statistics and methodology, Vol. 7, No. 4, p. 545-571. DOI:10.1093/jssam/smy024
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How Cross-Validation Can Go Wrong and What to Do About It
Neunhoeffer, M. & Sternberg, S. (2019): How Cross-Validation Can Go Wrong and What to Do About It. In: Political analysis, Vol. 27, p. 101-106. DOI:10.1017/pan.2018.39
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Collecting survey and smartphone sensor data with an app: opportunities and challenges around privacy and informed consent
Kreuter, F., Haas, G., Keusch, F., Bähr, S. & Trappmann, M. (2020): Collecting survey and smartphone sensor data with an app: opportunities and challenges around privacy and informed consent. In: Social science computer review, Vol. 38, No. 5, p. 533-549. DOI:10.1177/0894439318816389
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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
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Parametric bootstrap mean squared error of a small area multivariate EBLUP
Moretti, A., Shlomo, N. & Sakshaug, J. (2020): Parametric bootstrap mean squared error of a small area multivariate EBLUP. In: Communications in statistics - Simulation and computation, Vol. 49, No. 6, p. 1474-1486. DOI:10.1080/03610918.2018.1498889
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Paper, e-mail, or both?
Sakshaug, J., Vicari, B. & Couper, M. (2019): Paper, e-mail, or both? Effects of contact mode on participation in a web survey of establishments. In: Social science computer review, Vol. 37, No. 6, p. 750-765. DOI:10.1177/0894439318805160
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Within-household selection and dual-frame telephone surveys
Marlar, J., Chattopadhyay, M., Jones, J., Marken, S. & Kreuter, F. (2018): Within-household selection and dual-frame telephone surveys. A comparative experiment of eleven different selection methods. In: Survey Practice, Vol. 11, No. 2, p. 1-30. DOI:10.29115/SP-2018-0031
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Forecasting Elections in Multiparty Systems: A Bayesian Approach Combining Polls and Fundamentals
Stoetzer, L., Neunhoeffer, M., Gschwend, T., Munzert, S. & Sternberg, S. (2019): Forecasting Elections in Multiparty Systems: A Bayesian Approach Combining Polls and Fundamentals. In: Political analysis, Vol. 27, p. 255-262. DOI:10.1017/pan.2018.49
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Economic insecurity and the distribution of income volatility in the United States
Latner, J. (2019): Economic insecurity and the distribution of income volatility in the United States. In: Social science research, Vol. 77, p. 193-213. DOI:10.1016/j.ssresearch.2018.09.005
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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