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Harrison Quick, PhD

Harrison Quick

Assistant Professor
Epidemiology and Biostatistics
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PhD in Biostatistics, University of Minnesota


Dr. Quick received his PhD from the Division of Biostatistics at the University of Minnesota in 2013, where his research focused on Bayesian methods for spatial and spatiotemporal data analysis.  In addition, Dr. Quick has conducted research in the fields of data confidentiality, spatial epidemiology, and the application of Bayesian methods for environmental health and occupational exposure assessment.

Research Interests

  • Occupational Health
  • Spatial Analysis or GIS
  • Statistical Modeling
  • Urban Health
  • Bayesian Inference
  • Data Confidentiality


Quick, H., Huynh, T., and Ramachandran, G. (2016). “A method for constructing informative priors for Bayesian modeling of occupational hygiene data.” Accepted for publication in The Annals of Occupational Hygiene.

Casper, M, Kramer, M., Quick, H., Schieb, L., Vaughan, A.S., and Greer, S. (2016). “Changes in the geographic patterns of heart disease mortality in the United States 1973 to 2010.” Circulation, 133, 1171-1180.

Huynh, T., Quick, H., Ramachandran, G., Banerjee, S., Stenzel, M., Blair, A., Sandler, D., Engel, L., Kwok, R.K., and Stewart, P.A. (2016). “A comparison of the β-substitution method and a Bayesian approach for analyzing left-censored data for the GuLF STUDY.” The Annals of Occupational Hygiene, 60, 56-73.

Vaughan, A.S., Quick, H., Pathak, E., Kramer, M., and Casper, M. (2015). “Disparities in temporal and geographic patterns of declining heart disease mortality by race and sex in the United States, 1973-2010.” Journal of the American Heart Association, 4, doi: 10.1161/JAHA.115.002567. 

Quick, H., Holan, S.H., Wikle, C.K., and Reiter, J.P. (2015). “Bayesian marked point process modeling for generating fully synthetic public use data with point-referenced geography.” Spatial Statistics, 14, 439-451.

Quick, H., Carlin, B.P., and Banerjee, S. (2015).  “Heteroscedastic conditional auto-regression models for areally referenced temporal processes for analysing California asthma hospitalization data.” J. Roy. Statist. Soc., Ser. C (Applied Statistics), 64, 799-813.

Quick, H., Holan, S.H., and Wikle, C.K. (2015). “Zeros and ones: A case for suppressing zeros in sensitive count data with an application to stroke mortality.” Stat, 4, 227-234.

Quick, H., Banerjee, S., and Carlin, B.P. (2015).  “Bayesian modeling and analysis for gradients in spatiotemporal processes.”  Biometrics, 71, 575-584.

Visit Dr. Quick's personal website