James Wagner

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Research Associate Professor, ISR, Survey Research Center, Survey Methodology and JPSM, University of Maryland

James Wagner is an Associate Research Professor in the Survey Methodology Program. He received his PhD from the Michigan Program in Survey Methodology in 2008. He has worked on surveys for over 20 years and has extensive experience with sample design. He currently serves as the Chief Mathematical Statistician on the National Survey of Family Growth Continuous 2011-2019.

In addition to sample design, Wagner’s research interests include adaptive survey design to address potential nonresponse biases and indicators of survey data quality.


Research interests

Survey Nonresponse, Proxy Indicators for Nonresponse Bias, Survey Paradata, Bayesian Modeling of Survey Paradata, Adaptive and Responsive Survey Design, Survey Costs, Survey Cost Modeling

Selected Publications

Schouten, B., A. Peytchev and J. Wagner (2017). Adaptive Survey Design, CRC Press.

Wagner, J. and F. Hubbard (2014). "Producing Unbiased Estimates of Propensity Models During Data Collection." Journal of Survey Statistics and Methodology 2(3): 323-342.

Wagner, J. and K. Olson (2018). An Analysis of Interviewer Travel and Field Outcomes in Two Field Surveys. Journal of Official Statistics. 34: 211-237.

Wagner, J., B. T. West, H. Guyer, P. Burton, J. Kelley, M. P. Couper and W. D. Mosher (2017). The Effects of a Mid-Data Collection Change in Financial Incentives on Total Survey Error in the National Survey of Family Growth. Total Survey Error in Practice. P. P. Biemer, E. de Leeuw, S. Eckman, B. Edwards, F. Kreuter, L. E. Lyberg, N. C. Tucker and B. West, T. New York, Wiley.

Wagner, J., B. T. West, N. Kirgis, J. M. Lepkowski, W. G. Axinn and S. K. Ndiaye (2012). "Use of Paradata in a Responsive Design Framework to Manage a Field Data Collection." Journal of Official Statistics 28(4): 477-499.

Current research projects

Responsive Design for Efficient Survey Data Collection: An Education Program, Role: Co-PI

Advancing the Science of Responsive Design using Bayesian Methodology, Role: PI

National Survey of Family Growth, 2011-2019, Role: Chief Mathematical Statistician

Study to Assess Risk and Resillience in Servicemembers - Longitudinal Study (STARRS-LS.org), Role: UM PI