Publications: Statistical Methods (KEM)
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The impact of mixed modes on multiple types of measurement error
Cernat, A. & Sakshaug, J. (2020): The impact of mixed modes on multiple types of measurement error. In: Survey research methods, Vol. 14, No. 1, p. 79-91. DOI:10.18148/srm/2020.v14i1.7450
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Coverage error in data collection combining mobile surveys with passive measurement using apps
Keusch, F., Bähr, S., Haas, G., Kreuter, F. & Trappmann, M. (2023): Coverage error in data collection combining mobile surveys with passive measurement using apps. Data from a German national survey. In: Sociological methods & research, Vol. 52, No. 2, p. 841-878. DOI:10.1177/0049124120914924
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The impact of synthetic data generation on data utility with application to the 1991 UK samples of anonymised records
Taub, J., Elliot, M. & Sakshaug, J. (2020): The impact of synthetic data generation on data utility with application to the 1991 UK samples of anonymised records. In: Transactions on Data Privacy, Vol. 13, No. 1, p. 1-23.
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Nurse effects on measurement error in household biosocial surveys
Cernat, A. & Sakshaug, J. (2020): Nurse effects on measurement error in household biosocial surveys. In: BMC medical research methodology, Vol. 20, p. 1-9. DOI:10.1186/s12874-020-00922-2
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Variance Estimation by Linearisation for the At Risk of Poverty or Social Exclusion (AROPE) Rate
Zins, S. (2020): Variance Estimation by Linearisation for the At Risk of Poverty or Social Exclusion (AROPE) Rate. In: Austrian Journal of Statistics, Vol. 49, No. 1, p. 33-44. DOI:10.17713/ajs.v49i1.882
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Recent advances in probability-based and nonprobability survey research
Blom, A., Cornesse, C., Sakshaug, J. & Wenz, A. (2020): Recent advances in probability-based and nonprobability survey research. Editorial. In: Journal of survey statistics and methodology, Vol. 8, No. 1, p. 2-3. DOI:10.1093/jssam/smaa002
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The relationship between interviewer-respondent rapport and data quality
Sun, H., Conrad, F. & Kreuter, F. (2021): The relationship between interviewer-respondent rapport and data quality. In: Journal of survey statistics and methodology, Vol. 9, No. 3, p. 429-448. DOI:10.1093/jssam/smz043
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Zukunft der Aus- und Weiterbildung in der Markt- und Sozialforschung
Keusch, F. & Kreuter, F. (2020): Zukunft der Aus- und Weiterbildung in der Markt- und Sozialforschung. In: B. Keller, H.-W. Klein, A. Wachenfeld-Schell & T. Wirth (eds) (2020): Marktforschung für die Smart Data World, Wiesbaden, Springer Gabler p. 3-25. DOI:10.1007/978-3-658-28664-4_1
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Differential Privacy and Social Science: An Urgent Puzzle
Oberski, D. & Kreuter, F. (2020): Differential Privacy and Social Science: An Urgent Puzzle. In: Harvard Data Science Review, Vol. 2, No. 1, o. Sz. DOI:10.1162/99608f92.63a22079
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Ein Ansatz zur Vorhersage der Erststimmenanteile bei Bundestagswahlen
Neunhoeffer, M., Gschwend, T., Munzert, S. & Stoetzer, L. (2020): Ein Ansatz zur Vorhersage der Erststimmenanteile bei Bundestagswahlen. In: Politische Vierteljahresschrift, Vol. 61, No. 1, p. 111-130. DOI:10.1007/s11615-019-00216-3
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Integrating probability and nonprobability samples for survey inference
Wiśniowski, A., Sakshaug, J., Perez Ruiz, D. & Blom, A. (2020): Integrating probability and nonprobability samples for survey inference. In: Journal of survey statistics and methodology, Vol. 8, No. 1, p. 120-147. DOI:10.1093/jssam/smz051
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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
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Die digitale Herausforderung
Horn, C. & Kreuter, F. (2020): Die digitale Herausforderung. Tipping Points, die Ihr Unternehmen verändern werden. Freiburg: Haufe, 324 p.
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A review of conceptual approaches and empirical evidence on probability and nonprobability sample survey research
Cornesse, C., Blom, A., Dutwin, D., Krosnick, J., Leeuw, E., Legleye, S., Pasek, J., Phillips, B., Pennay, D., Phillips, B., Sakshaug, J., Struminskaya, B. & Wenz, A. (2020): A review of conceptual approaches and empirical evidence on probability and nonprobability sample survey research. In: Journal of survey statistics and methodology, Vol. 8, No. 1, p. 4-36. DOI:10.1093/jssam/smz041
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New Data Sources in Social Science Research
Ashley, A., Bach, R., Keusch, F. & Kreuter, F. (2021): New Data Sources in Social Science Research. Things to Know Before Working With Reddit Data. In: Social science computer review, Vol. 39, No. 5, p. 943-960. DOI:10.1177/0894439319893305
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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. (2020): Learning from mouse movements: Improving questionnaire and respondents' user experience through passive data collection. In: P. C. Beatty, D. Collins, L. Kaye, J. L. Padilla, G. Willis & A. Wilmot (Eds.) (2020): Advances in questionnaire design, development, evaluation and testing, Nürnberg, p. 403-426. DOI:10.1002/9781119263685.ch16
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The salience of survey burden and its effect on response behavior to skip questions
Kreuter, F., Eckman, S. & Tourangeau, R. (2020): The salience of survey burden and its effect on response behavior to skip questions. Experimental results from telephone and web surveys. In: P. C. Beatty, D. Collins, L. Kaye, J. L. Padilla, G. Willis & A. Wilmot (Eds.) (2020): Advances in questionnaire design, development, evaluation and testing, Nürnberg, p. 213-228. DOI:10.1002/9781119263685.ch9
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Does benefit framing improve record linkage consent rates?
Sakshaug, J., Stegmaier, J., Trappmann, M. & Kreuter, F. (2019): Does benefit framing improve record linkage consent rates? A survey experiment. In: Survey research methods, Vol. 13, No. 3, p. 289-304. DOI:10.18148/srm/2019.v13i3.7391
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What do we know about voters who say "don't know" in election polls?
Purdam, K. & Sakshaug, J. (2019): What do we know about voters who say "don't know" in election polls? In: The Conversation No. 06.12.2019, o.Sz.
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Change through data: a data analytics training program for government employees
Kreuter, F., Ghani, R. & Lane, J. (2019): Change through data: a data analytics training program for government employees. In: Harvard Data Science Review, Vol. 1, No. 2, p. 26 S. DOI:10.1162/99608f92.ed353ae3