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Professor Joe Sakshaug

Research interests

Main research interests: survey methodology, non-response and missing data techniques, measurement error, big data, experimental design, combining information from multiple data sources, mixed-mode data collection, confidentiality and disclosure limitation, small area estimation, occupation coding, surveying sensitive topics, longitudinal studies, digital behavioural data, cross-cultural research

Applied interests: labour market research, public opinion, health and wellbeing, social inequalities, education, COVID-19

Research methodology: Bayesian inference, causal inference, structural equation modelling, machine learning, multilevel modelling, multiple imputation, record linkage, data science methods

Qualifications

  • PhD in Survey Methodology, University of Michigan
  • MSc in Survey Methodology, University of Michigan
  • BA in Mathematics, University of Washington

Selected current projects

  • Evaluating Data Sources for Research into Political Reforms: (Non)probability Online Surveys and Big Data (German Science Foundation, 2018-2022)
  • Enhancing the Quality and Utility of Longitudinal Data for Education Research (German Science Foundation, 2018-2019)
  • Exploring Synthetic Record Linkage for Administrative Databases (Economic and Social Research Council, National Centre for Research Methods, 2018)
  • Combining Probability and Non-Probability Samples to Reduce Survey Errors and Survey Costs: A Proof-of-Concept Study (British Academy / Leverhulme Trust, 2017-2018)
  • Feasibility Study Regarding Methodology, Design and Mode of the European Company Survey (Eurofound, subcontractor, 2016-2017)
  • Imputation and Record Linkage Strategies for Educational Data Collected from Surveys and Administrative Sources (German Science Foundation, 2015-2018).
  • Alternative Approaches to the Analysis of Complex Sample Survey Data: Applying State-of-the-Art Methods to NCSES Surveys (US National Science Foundation 2014-2017)

All projects

Selected publications

Books:
  • Snijkers, G., Bavdaž, M., Bender, S., Jones, J., MacFeeley, S., Sakshaug, J.W., Thompson, K.J., and Van Delden, A. (Eds.) (In Press). Advances in Business Statistics, Methods and Data Collection. John Wiley and Sons.
  • Cernat, A., and Sakshaug, J.W. (Eds.) (2021). Measurement Error in Longitudinal Data. Oxford University Press. 
  • Atkinson, P.A., Delamont, S., Cernat, A., Sakshaug, J.W., and Williams, R.A. (Eds.) (2021). SAGE Research Methods Foundations: An Encyclopedia. Sage Publications.
Journal articles:
  • Küfner, B., Sakshaug, J.W., and Zins, S. (2022). Establishment Survey Participation During the COVID-19 Pandemic. Journal for Labour Market Research, 56(18), 1-18.
  • Küfner, B., Sakshaug, J.W., and Zins, S. (2022). Analyzing Establishment Survey Nonresponse Using Administrative Data and Machine Learning. Journal of the Royal Statistical Society: Series A (Statistics in Society), 182(Suppl. 2), S310-S342.
  • Sakshaug, J.W. (2022). Reducing Nonresponse and Data Linkage Consent Bias in Large-Scale Panel Surveys. Forum for Health Economics & Policy, 25(1-2), 41-55.
    • Kosyakova, Y., Olbrich, L., Sakshaug, J.W., and Schwanhäuser, S. (2022). Positive Learning or Deviant Interviewing? Mechanisms of Experience on Interviewer Behavior. Journal of Survey Statistics and Methodology, 10(2), 249-275.
      • Sakshaug, J.W., Cernat, A., Silverwood, R.J., Calderwood, L., and Ploubidis, G.B. (2022). Measurement Equivalence in Sequential Mixed-Mode Surveys. Survey Research Methods, 16(1), 29-43.
      • Schwanhäuser, S., Sakshaug, J.W., and Kosyakova, Y. (2022). How to Catch a Falsifier: Comparison of Statistical Detection Methods for Interviewer Falsification. Public Opinion Quarterly, 86(1), 51-81.
      • Johnson, R.M., Crifasi, C., Anderson-Goodell, E.M., Wiśniowski, A., Sakshaug, J.W., Thrul, J., and Owens, M. (2021). Differences in Beliefs about COVID-19 by Gun Ownership: A Cross-Sectional Survey of Texas Adults. BMJ Open, 11:e048094.
      • Cernat, A., and Sakshaug, J.W. (2021). Understanding the Patterns of Mode Switching in Longitudinal Studies. Survey Research Methods, 15(3), 281-298.
      • Büttner, T.J.M., Sakshaug, J.W., and Vicari, B. (2021). Evaluating the Utility of Linked Administrative Data for Nonresponse Bias Adjustment in a Piggyback Longitudinal Survey. Journal of Official Statistics, 37(4), 837-864.
      • König, C., Sakshaug, J.W., Stegmaier, J., and Kohaut, S. (2021). Trends in Establishment Survey Nonresponse Rates and Nonresponse Bias: Evidence from the 2001-2017 IAB Establishment Panel. Journal of Official Statistics, 37(4), 931-953.
      • Peycheva, D.N., Sakshaug, J.W., and Calderwood, L. (2021). Occupation Coding During the Interview in a Web-First Sequential Mixed-Mode Survey. Journal of Official Statistics, 37(4), 981-1007.
      • Küfner, B., Sakshaug, J.W., and Zins, S. (2021). More Clarification, Less Item Nonresponse in Establishment Surveys? A Split-Ballot Experiment. Survey Research Methods, 15(2), 195-206.
      • Sakshaug, J.W., Schmucker, A., Kreuter, F., Couper, M.P., and Holtmann, L. (2021). Respondent Understanding of Data Linkage Consent. Survey Methods: Insights from the Field, 5, 1-15.
      • Cernat, A., Sakshaug, J.W., Chandola, T., Nazroo, J., and Shlomo, N. (2021). Nurse Effects on Non-Response in Survey-Based Biomeasures. International Journal of Social Research Methodology, 24(4), 487-499.
      • Cernat, A., and Sakshaug, J.W. (2021). Interviewer Effects in Biosocial Survey Measurements. Field Methods, 33(3), 236-252.
      • Moretti, A., Shlomo, N., and Sakshaug, J.W. (2021). Small Area Estimation of Latent Economic Well-being. Sociological Methods and Research, 50(4), 1660-1693.
      • Bavdaž, M., Snijkers, G., Sakshaug, J.W., Brand, T., Haraldsen, G., Kurban, B., Saraiva, P., and Willimack, D.K. (2020). Business Data Collection Methodology: Current State and Future Outlook. Statistical Journal of the IAOS, 36(3), 741-756.
      • Sakshaug, J.W., Beste, J., Coban, M., Fendel, T., Haas, G-C., 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., and Zins, S. (2020). Impacts of the COVID-19 Pandemic on Labor Market Surveys at the German Institute for Employment Research. Survey Research Methods, 14(2), 229-233.

      All publications

      Editorial activities

      • Associate Editor, Journal for Labour Market Research (2021-)
      • Associate Editor, Journal of Survey Statistics and Methodology (2017-)
      • Associate Editor, Survey Research Methods (2017-)
      • Associate Editor, Journal of Official Statistics (2016-)
      • Co-Guest Editor, Public Opinion Quarterly (Forthcoming), Special Issue on “Augmenting Surveys with Paradata, Administrative Data, and Contextual Data”
      • Co-Guest Editor, Journal of Survey Statistics and Methodology (Forthcoming), Special Issue on “Recent Advances in Data Integration”
      • Co-Guest Editor, Journal of Survey Statistics and Methodology (2020), Special Issue on “Advances in Probability-Based and Nonprobability Survey Research”
       

       

      Joe SakshaugProfessor

      Institute for Employment Research
      University of Warwick
      Coventry CV4 7AL

      Tel: +44(0)24 76 550986
      Fax: +44(0)24 76 524241

      Joe.Sakshaug@warwick.ac.uk