Erik Nordheim

Erik Nordheim

Professor of Statistics
1110 Med Sci, 1300 University Ave.
(608) 263-5812

Curriculum Vitae

Selected Publications:
Barzen, J. and more than 20 others, including E.V. Nordheim. 2012. Persistent Organic Pollutants in Wetlands of the Mekong Basin. (refereed monograph)

Burgette, L.F., E.V. Nordheim. 2012. The trace restriction: An alternative identification strategy for the Bayesian multinomial probit model. Journal of Business & Economic Statistics 30; pp404-410.

Taylor, B.J., E.V. Nordheim, R.L. Jeanne. 2012. Allocation of colony-level foraging effort in Vespula germanica in response to food resource quantity, quality, and associated olfactory cues. Ethology 118: 594-605.

Schueller, T.I., E.V. Nordheim, B.J. Taylor, R.L. Jeanne. 2010. The cues have it: nest-based, cue-mediated recruitment to carbohydrate resources in a swarm-founding social wasp. Naturwissenshaften 97:1017-1022.

Li. J.L., C.M. Zhang, K.A. Doksum, E.V. Nordheim. 2010. Simultaneous Confidence Intervals for Semiparametric Logistic Regression and Confidence Regions fort the Multi-Dimensional Effective Dose. Statistica Sinica 20: 637-659.

Center for Demography and Ecology
Center for Demography of Health and Aging
Sociology Affiliated Faculty

Research Interest Statement:
As leader of CDE’s Statistics subcore, Nordheim provides provided statistical consulting to researchers in CDE. He has recently worked with Prof. Giovanna Merli on a study of respondent driven sampling (RDS), to support her ongoing research on female sex workers in Shanghai China. The findings to date suggest that violations of the rather stringent assumptions underlying RDS can lead to inaccurate estimation with this method. Thus, substantial improvement in methods for sampling hidden populations is needed. Efforts in this direction are underway. A second project is work with Lane Burgette, a graduate student supported by CDE, developing new methods for Bayesian multinomial probit switching models. This work, which was motivated by a problem stemming from research being done by Prof. James Raymo on individuals’ future interests regarding work status (full-time, part-time, not working). The solution to this problem has required extending some of the existing selection model work in new directions with quite intricate modeling using Markov Chain Monte Carlo methods. This work expands the statistical toolbox for complex switching models.

Nordheim has organized several workshops on statistical issues relevant to demography research (see Progress Report), such as propensity scoring and Bayesian Model Averaging. These are aimed at researchers in CDE along and also in allied fields.