Publications: Statistical Methods (KEM)
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Nurse Effects on Non-Response in Survey-Based Biomeasures
Cernat, A., Sakshaug, J., Chandola, T., Nazroo, J. & Shlomo, N. (2021): Nurse Effects on Non-Response in Survey-Based Biomeasures. In: International Journal of Social Research Methodology, Vol. 24, No. 4, p. 487-499. DOI:10.1080/13645579.2020.1832737
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How effective are enforcement measures for compliance with the minimum wage?
Bossler, M., Jaenichen, U. & Schächtele, S. (2022): How effective are enforcement measures for compliance with the minimum wage? Evidence from Germany. In: Economic and Industrial Democracy, Vol. 43, No. 2, p. 943-971. DOI:10.1177/0143831X20962193
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The R Package hmi: A Convenient Tool for Hierarchical Multiple Imputation and Beyond
Speidel, M., Drechsler, J. & Jolani, S. (2020): The R Package hmi: A Convenient Tool for Hierarchical Multiple Imputation and Beyond. In: Journal of statistical software, Vol. 95, No. 9, p. 1-48. DOI:10.18637/jss.v095.i09
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Linking Surveys with Big Data
Sakshaug, J. (2020): Linking Surveys with Big Data. Issues of Consent. In: B. Klumpe, J. Schröder & M. Zwick (Hrsg.) (2020): Qualität bei zusammengeführten Daten - Befragungsdaten, Administrative Daten, neue digitale Daten: Miteinander besser?, Wiesbaden, Springer VS p. 163-173. DOI:10.1007/978-3-658-31009-7_12
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TippingSens: An R Shiny Application to Facilitate Sensitivity Analysis for Causal Inference Under Confounding
Haensch, A., Drechsler, J. & Bernhard, S. (2020): TippingSens: An R Shiny Application to Facilitate Sensitivity Analysis for Causal Inference Under Confounding. (IAB-Discussion Paper 29/2020), Nürnberg, 39 p.
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Data linkage
Antoni, M. & Sakshaug, J. (2020): Data linkage. In: P. A. Atkinson, A. Cernat, S. Delamont, J. Sakshaug & R. A. Williams (Eds.) (2020): SAGE Research Methods foundations, p. 1-18. DOI:10.4135/9781526421036931838
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Secure Matrix Computation: A Viable Alternative to Record Linkage?
Drechsler, J. & Klein, B. (2020): Secure Matrix Computation: A Viable Alternative to Record Linkage? In: J. Domingo-Ferrer & K. Muralidhar (Hrsg.) (2020): Privacy in Statistical Databases, Cham, p. 240-254. DOI:10.1007/978-3-030-57521-2_17
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Applying data synthesis for longitudinal business data across three countries
Alam, M., Dostie, B., Drechsler, J. & Vilhuber, L. (2020): Applying data synthesis for longitudinal business data across three countries. In: Statistics in transition, Vol. 21, No. 4, p. 212-236. DOI:10.21307/stattrans-2020-039
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Combining Active and Passive Mobile Data Collection: A Survey of Concerns
Keusch, F., Struminskaya, B., Kreuter, F. & Weichbold, M. (2020): Combining Active and Passive Mobile Data Collection: A Survey of Concerns. In: C. A. Hill, P. P. Biemer, T. D. Buskirk, L. Japec, A. Kirchner, S. Kolenikov & L. E. Lyberg (Eds.) (2020): Big Data Meets Survey Science: A Collection of Innovative Methods, New York, Wiley p. 657-682. DOI:10.1002/9781118976357.ch22
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Effects of incentives in smartphone data collection
Haas, G., Kreuter, F., Keusch, F., Trappmann, M. & Bähr, S. (2020): Effects of incentives in smartphone data collection. In: C.A. Hill, P.P. Biemer, T. Buskirk, L. Japec, A. Kirchner, S. Kolenikov & L.E. Lyberg (Eds.) (2020): Big Data Meets Survey Science, p. 387-414. DOI:10.1002/9781118976357.ch13
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Measuring the Strength of Attitudes in Social Media Data
Amaya, A., Bach, R., Kreuter, F. & Keusch, F. (2020): Measuring the Strength of Attitudes in Social Media Data. In: C.A. Hill, P.P. Biemer, T. Buskirk, L. Japec, A. Kirchner, S. Kolenikov & L.E. Lyberg (Eds.) (2020): Big Data Meets Survey Science: A Collection of Innovative Methods, p. 163-192. DOI:10.1002/9781118976357.ch5
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Acceptability of app-based contact tracing for COVID-19: Cross-country survey evidence
Altmann, S., Milsom, L., Zillessen, H., Blasone, R., Gerdon, F., Bach, R., Kreuter, F., Nosenzo, D., Toussaert, S. & Abeler, J. (2020): Acceptability of app-based contact tracing for COVID-19: Cross-country survey evidence. In: JMIR mhealth and uhealth, Vol. 8, No. 8, p. 1-9. DOI:10.2196/19857
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Business Data Collection Methodology: Current State and Future Outlook
Bavdaž, M., Snijkers, G., Sakshaug, J., Brand, T., Haraldsen, G., Kurban, B., Saraiva, P. & Willimack, D. (2020): Business Data Collection Methodology: Current State and Future Outlook. In: Statistical Journal of the IAOS, Vol. 36, No. 3, p. 741-756. DOI:10.3233/SJI-200623
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Missing Data and Other Measurement Quality Issues in Mobile Geolocation Sensor Data
Bähr, S., Haas, G., Keusch, F., Kreuter, F. & Trappmann, M. (2022): Missing Data and Other Measurement Quality Issues in Mobile Geolocation Sensor Data. In: Social science computer review, Vol. 40, No. 1, p. 212-235. DOI:10.1177/0894439320944118
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Mental distress during the COVID-19 pandemic among US adults without a pre-existing mental health condition: Findings from American trend panel survey
Holingue, C., Badillo-Goicoechea, E., Riehm, K., Veldhuis, C., Thrul, J., Johnson, R., Fallin, M., Kreuter, F., Stuart, E. & Kalb, L. (2020): Mental distress during the COVID-19 pandemic among US adults without a pre-existing mental health condition: Findings from American trend panel survey. In: Preventive Medicine, Vol. 139, p. 1-8. DOI:10.1016/j.ypmed.2020.106231
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Associations Between Media Exposure and Mental Distress Among U.S. Adults at the Beginning of the COVID-19 Pandemic
Riehm, K., Holingue, C., Kalb, L., Bennett, D., Kapteyn, A., Jiang, Q., Veldhuis, C., Johnson, R., Fallin, M., Kreuter, F., Stuart, E. & Thrul, J. (2020): Associations Between Media Exposure and Mental Distress Among U.S. Adults at the Beginning of the COVID-19 Pandemic. In: American Journal of Preventive Medicine, Vol. 59, No. 5, p. 630-638. DOI:10.1016/j.amepre.2020.06.008
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The Impact of Nurse Continuity on Biosocial Survey Participation
Cernat, A. & Sakshaug, J. (2020): The Impact of Nurse Continuity on Biosocial Survey Participation. In: Survey Methods: Insights from the Field, p. 1-14. DOI:10.13094/SMIF-2020-00010
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Considering interviewer and design effects when planning sample sizes
Zins, S. & Burgard, J. (2020): Considering interviewer and design effects when planning sample sizes. In: Survey Methodology, Vol. 46, No. 1, p. 93-119.
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Impacts of the COVID-19 Pandemic on Labor Market Surveys at the German Institute for Employment Research
Sakshaug, J., Beste, J., Coban, M., Fendel, T., Haas, G., Hülle, S., Kosyakova, Y., König, C., Kreuter, F., Küfner, B., Müller, B., Osiander, C., Schwanhäuser, S., Stephan, G., Vallizadeh, E., Volkert, M., Wenzig, C., Westermeier, C., Zabel, C. & Zins, S. (2020): Impacts of the COVID-19 Pandemic on Labor Market Surveys at the German Institute for Employment Research. In: Survey research methods, Vol. 14, No. 2, p. 229-233. DOI:10.18148/srm/2020.v14i2.7743
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Partnering with a global platform to inform research and public policy making
Kreuter, F., Barkay, N., Bilinski, A., Bradford, A., Chiu, S., Eliat, R., Fan, J., Galili, T., Haimovich, D., Kim, B., LaRocca, S., Li, Y., Morris, K., Presser, S., Sarig, T., Salomon, J., Stewart, K., Stuart, E. & Tibshirani, R. (2020): Partnering with a global platform to inform research and public policy making. What needs to be in place to make a global COVID-19 survey work? In: Survey research methods, Vol. 14, No. 2, p. 159-163. DOI:10.18148/srm/2020.v14i2.7761