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Mr. Frost Hubbard

Mr. Frost Hubbard is a Principal Research Associate in IMPAQ's Survey Division. He provides leadership to all aspects of survey methodology and data collection including the design and implementation of rigorous and efficient sampling methods, data collection strategies, and analysis and interpretation of primary and secondary data.

Expertise

Mr. Hubbard has more than ten years of experience in survey research with an emphasis in sample design and management, survey methodology, questionnaire development, project management and data analysis. He has served as a lead sampling statistician or survey methodologist for several large, multistage, nationally representative surveys in a number of different research areas, including education, health, and economics.

Clients

Mr. Hubbard has worked with a wide range of clients including the Centers for Medicare and Medicaid Services, the U.S. Department of Health and Human Services, the National Institute of Aging, the Robert Wood Johnson Foundation, and the National Science Foundation.

Prior Experience

Prior to joining IMPAQ, Mr. Hubbard held positions as Director of the Statistics and Methodology Unit and Senior Research Associate at the University of Michigan’s Institute for Social Research.

Education

Dr. Hubbard earned his M.S. in Survey Methodology from the University of Michigan in 2006. He is a member of the American Association for Public Opinion Research (AAPOR) and the American Statistical Association. He has published and/or presented his work in multiple book chapters, peer-reviewed journals, and conferences.

Previous Papers and Publications

Publications

West, B.T., Kirchner, A., Hochfellner, D., Bender, S., Nichols, E.M., Mulry, M., Childs, J.H., Holmberg, A., Bycroft, C. Benson, G. & Hubbard, F. (forthcoming). Establishing Infrastructure for the Use of Big Data to Understand Total Survey Error. In P. Biemer, E. de Leeuw, B. Edwards, S. Eckman, F. Kreuter, L. Lyberg, C. Tucker and B.T. West (Eds.), Total Survey Error in Practice. (pp.459-486). Hoboken, NJ: John Wiley & Sons.

West, B.T., Wagner, J., Gu, H. & Hubbard, F. (2015). The Utility of Alternative Commercial Data Sources for Survey Operations and Estimation: Evidence from the National Survey of Family Growth. Journal of Survey Statistics and Methodology, 3(2), 240-264.

Wagner, J., Valliant, R., Hubbard, F. & Jiang, L. (2014). Level-of-Effort Paradata and Nonresponse Adjustment Models for a National Face-to-Face Survey. Journal of Survey Statistics and Methodology, 3(2), 240-264

Valliant, R., Hubbard, F., Lee, S. & Chang, W. (2014). Efficient Use of Commercial Lists in Household Sampling. Journal of Survey Statistics and Methodology, 2(2), 182-209.

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

Hubbard, F., Lin, Y., Zahs, D. & Hu, M. (2016) Chapter 5: Sample Design. In Cross Cultural Survey Guidelines. Retrieved from http://www.ccsg.isr.umich.edu/index.php/chapters/sample-design-chapter

Orlowski, R. A., Hubbard, F., Blasczyk, E., and Zahs, D. (2016) Chapter 14: Data Processing and Statistical Adjustment.  In Cross-Cultural Survey Guidelines. Retrieved from http://www.ccsg.isr.umich.edu/index.php/chapters/data-processing-and-statistical-adjustment-chapter

Mohler, P.P., Hansen, S.E., Pennell, B-E., Thomas, W., Wackerow, J. & Hubbard, F. (2010). Chapter 16: A Survey Process Quality Perspective on Documentation. In: J.A. Harkness, M. Braun, B. Edwards, T.P. Johnson, L. Lyberg, P.P. Mohler, B-E. Pennell, & T.W. Smith (Eds.), Survey Methods in Multinational, Multiregional and Multicultural Contexts (pp.299-314). Hoboken, NJ: John Wiley & Sons.

Mohler, P.P., Pennell, B-E. & Hubbard, F. (2008). Survey Documentation: Toward Professional Knowledge Management in Sample Surveys.” In: E.D. de Leeuw, J.J. Hox, & D.A.Dillman (Eds.), International Handbook of Survey Methodology (pp.403-420). New York/London: Lawrence Erlbaum Associates/Taylor & Francis Group.

Heeringa, S.G., Wells, J.E., Hubbard, F., Mneimneh, Z.N., Chiu, W., Simpson, N.A. & Berglund, P.A. (2008). Sample Designs and Sampling Procedures. In: R.C. Kessler & T.B. Ustun (Eds.), The WHO World Mental Health Surveys: Global Perspectives on the Epidemiology of Mental Disorders (pp.14-32). Cambridge University Press.

Presentations

Guzman, D., Lee, S., Valliant, R., Burton, P. & Hubbard, F. (2016, August). Alternative Variance Component Analyses for a Three-Stage Sample Design. Paper presented at the Joint Statistical Meetings, Chicago, IL.

Hubbard, F., Tomlin, D. & Camelo, T. (2014, August). Seeking to Reduce Motivated Underreporting to the Health and Retirement Study Screening Interview. Paper presented at the Joint Statistical Meetings, Boston, MA.

Hubbard, F., West, B.T., Wagner, J. & Gu, H. (2014, May). The Utility of Alternative Commercial Data Sources for Survey Operations and Estimation: Evidence from the National Survey of Family Growth. Paper presented at the American Association for Public Opinion Research Conference, Anaheim, CA.

Hubbard, F., Wagner, J.R., Gu, H. & Chang, C. (2013, May). Building a More Powerful Model to Predict Areas Where USPS Based Address Lists May Be Used in Place of Traditional Listing. Paper presented at the American Association for Public Opinion Research Conference, Boston, MA.

Wagner, J.R. & Hubbard, F. (2013, May). Using Propensity Models during Data Collection for Responsive Designs: Issues with Estimation. Paper presented at the American Association for Public Opinion Research Conference, Boston, MA.

Hubbard, F., Kelley, J., Smith, J. & Zhang, X. (2013, May). A Demonstration of the University of Michigan Survey Research Center’s Electronic Listing Program. Live demonstration at the American Association for Public Opinion Research Conference, Boston, MA.

Hubbard, F., Antoun, C. & Conrad, F.G. (2012, July). Conversational Interviewing and the Comprehension of Opinion Questions. Paper presented at the RC33 Eighth International Conference on Social Science Methodology, Sydney, Australia.

Schroeder, H., Hubbard, F. & Szmigiel, K. (2012, August) Identifying Survey Interviewer Applicants with a High Probability of Early Termination. Paper presented at the Joint Statistical Meetings, San Diego, CA.

Couper, M.P., Ofstedal, M.B., Hubbard, F. & Weir, D. (2012, July). Mode Effects in a Panel Study. Paper presented at the International Panel Survey Methods Workshop, Melbourne, Australia.

Hubbard, F., Wagner, J.R., Guyer, H., Arrieta, J. & Dworak, P. (2011, August). An Attempt to Reduce Survey Costs and Errors Using Logistic Regression and Paradata. Paper presented at the Joint Statistical Meetings, Miami, FL.

Hubbard, F., Guyer, H., Gu, H. & Arrieta, J. (2011, March). Determining Best Contact Windows for Different Survey Populations and Implementing an Optimal Call Window Responsive Design Plan during Data Collection. Presentation at the Federal CASIC Workshops, Washington, DC.

Jans, M., Hubbard, F. & Duffey, B. (2010, October). Paradata, Metadata, Auxiliary Data, and other Data about Data Studying Survey Costs and Errors in the New Millennium. Paper presented at the Southern Association for Public Opinion Research Conference, Raleigh, NC.

Hubbard, F., Couper, M.P., Wagner, J.R., Gu, H., Benson, G. & Schulz, P. (2010, May). Creating Paradata Dashboards: Developing a Tool to Help Monitor and Reduce Survey Costs and Errors. Presentation and the International Field Directors and Technologies Conference, Chicago, IL.

Matuzak, J., Hubbard, F. & Carn, L. (2010, May). Determining the Meaning of Prerecorded Cell Phone Carrier Messages. Presentation at the International Field Directors and Technology Conference, Chicago, IL.

Hubbard, F. (2006, November). Are Indicators of At Home Patterns Related to the Likelihood of Contact for Cell Phone Surveys? Paper accepted for Midwest Association for Public Opinion Research Conference, Chicago, IL.

Conrad, F.G., Park, H., Singer, E., Couper, M.P., Hubbard, F. & Groves, R. (2006, May). Impact of Disclosure Risk on Survey Participation Decisions. Paper presented at the American Association for Public Opinion Research Conference, Montreal, Canada.