Megan Dailey Higgs, Ph.D.

Associate Professor of Statistics



  • Ph.D. (Statistics), Department of Statistics, Colorado State University, Fort Collins, CO, 2007
  • M.S. (Statistics), Department of Statistics, Oregon State University, Corvallis, OR, 2002
  • M.S. (Kinesiology), University of Nevada, Las Vegas, Las Vegas, NV, 1998
  • B.S. (Biology), Montana State University, Bozeman, MT, 1996


2014-2015 Academic year

  • STAT 411/511: Methods of Data Analysis I
  • STAT 412/512: Methods of Data Analysis II
  • STAT 532: Bayesian Statistics
  • STAT 510: Statistical Consulting Seminar
  • STAT 575: M.S. Writing Projects coordinator

Research Interests and Funding

  • I believe my most valuable place as a statistician is working alongside other researchers to improve study design, data analysis, and the inferential statements made from data. Therefore, my research is driven by collaboration with other scientists, mostly in the ecological and environmental sciences.
  • Funding sources:
    • Interagency Grizzly Bear Study Team, United State Geological Survey
    • Alaska Fisheries Science Center, National Marine Mammal Laboratory, National Oceanic and Atmospheric Administration
    • United States Geological Survey (USGS)
    • Grand Teton National Park


  • My CV (February 2015)
  • ASA American Statistical Association
  • TIES The International Environmetrics Society (TIES)
  • MT chapter of the ASA Montana Chapter of the ASA
  • CWIS The Caucus for Women in Statistics
  • CAUSEweb Consortium for the Advancement of Undergraduate Statistics Education
  • R-project R Project for Statistical Computing (free software environment)
  • OpenBUGS Software for Bayesian inference Using Gibbs Sampling
  • JAGS Just Another Gibbs Samper
  • Stan Package for Bayesian inference using the No-U-Turn sampler
  • Andrew Gelman's blog
  • Chambert, T., Rotella, J.J., and Higgs, M.D. (2014). Use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates. Ecology and Evolution, 4(8), pp 1389-1397. doi: 10.1002/ece3.993.
  • van Manen, F., Ebinger, M.R., Haroldson, M.A., Harris, R.B., Higgs, M.D., Cherry, J.S., White, G.C., and Schwartz, C.C. (2014). Re-evaluation of Yellowstone Grizzly Bear Population Dynamics not Supported by Empirical Data: Response to Doak & Cutler. Online in Conservation Letters. doi:10.1111/conl.12095. 

Selected Publications

  • Bandyopadhyay, P.S., Bennett, J.G., and Higgs, M.D. (2014) How to undermine underdetermination? Online in Foundations of Science. doi: 10.1007/s10699-014-9353-3.
  • Higgs, M.D., Link, W.A., White, G.C., Haroldson, M.A., and Bjornlie, D.A. (2013). Insights into the latent multinomial model through mark-resight data on female grizzly bears with cubs-of-the-year. The International Journal of Agricultural and Biological Statistics, doi: 0.1007/s13253-013-0148-8. Link to paper
  • Higgs, M.D. (2013). Do we really need the s-word? American Scientist, 101:1, pp. 6-9. Link to paper
  • Chambert, T., Rotella, J.J., Higgs, M.D., and Garrott, R.A. (2013) Individual heterogeneity in reproductive rates and cost of reproduction in a long-lived vertebrate. Ecology and Evolution, doi: 10.1002/ece3.615.  Link to paper
  • Brennan, A., Cross, P.C., Higgs, M.D., Beckman, J.P., Klaver, R.W., Scurlock, B.M., and Creel, S. (2013). Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology. Ecological Applications, 23(3), pp. 643-653. doi:
  • Powell, J.H., Kalinowski S.T., Higgs, M.D., Ebinger, M.R., Vu, N.V., and Cross P.C. (2013). Microsatellites indicate minimal barriers to mule deer Odocoileus hemionus dispersal across Montana, USA. Wildlife Biology, 19(1), pp. 102-110. doi:
  • Brummer, T.B., Maxwell, B.D., Higgs, M.D., and Rew, L.J. (2013). Implementing and interpreting local scale invasive species distribution models. Diversity and Distributions. doi: 10.1111/ddi.12043 Link to paper
  • Cain, S.L., Higgs, M.D., Roffe, T.J., Monfort, S.L., and Berger, J. (2012). Using fecal progestagens and logistic regression to enhance individual bison pregnancy status. Wildlife Society Bulletin, 36(4), pp. 631-640. doi: 10.1002/wsb.178  Link to paper
  • Higgs, M.D. and Ver Hoef, J. M. (2012). Discretized and aggregated: Modeling dive depth of harbor seals from ordered categorical data with temporal autocorrelation. Biometrics, 68, pp. 965-974. doi: 10.1111/j.1541-0420.2011.01710.x Link to paper
  • Higgs, M.D. and Hoeting, J.A. (2010). A clipped latent-variable model for spatially correlated ordered categorical data.Computational Statistics and Data Analysis, 54(8), pp. 1999-2011,
  • Dailey, M., Gitelman, A.I., Ramsey, F.L., and Starcevich, S. (2007). Habitat selection models to account for seasonal persistence in radio telemetry data. Environmental and Ecological Statistics, 14(1), pp. 55-58. doi: 10.1007/s10651-006-0006-8. Link to paper