Jean Opsomer

Vice President; Statistical Fellows Committee Co-Chair

Jean Opsomer, Ph.D., is a senior statistician with extensive experience applying statistical methods to answer research questions. He is responsible for the statistical and survey methodology of several large-scale survey projects.

Dr. Opsomer is an Adjunct Professor in the Department of Mathematics at University of Maryland, College Park. Previously, he was a faculty member in the Departments of Statistics at Colorado State University and Iowa State University. His recent research has focused on the introduction of shape-constrained and nonparametric methods in survey estimation and on several interdisciplinary projects with survey components on a range of topics (higher education, public health, nutrition, employment, fisheries management, methane emissions, forest health, and agricultural erosion). The author or coauthor of 70 peer-reviewed articles, he has introduced a number of influential novel statistical methodologies into survey estimation. His methodological and theoretical work is frequently motivated by questions that arise within federal statistical agencies with which he has long-term collaborations.

Dr. Opsomer is a Fellow of the American Statistical Association (ASA) and the Institute of Mathematical Statistics and an Elected Member of the International Statistical Institute. He is the recipient of the Carver Medal of the Institute of Mathematical Statistics. In recognition of his contributions to the field, Dr. Opsomer has been named a Westat Senior Statistical Fellow and co-chairs the Statistical Fellows Committee, which provides consultation on important survey statistics issues and addresses recent advances in applied statistics.


Ph.D., Operations Research , Cornell University
M.B.A., Finance, University of Chicago
M.S., Management Engineering, Katholieke Universiteit Leuven, Belgium

Areas of Expertise

Selected Publications

Olson K., Smyth J.D., Horwitz R., Keeter S., Lesser V., Marken S., Mathiowetz N.A., McCarthy J.S., O'Brien E., Opsomer J.D., Steiger D., Sterrett D., Su J., Suzer-Gurtekin Z.T., Turakhia C., and Wagner J. (2020).

Transitions from telephone surveys to self-administered and mixed-mode surveys: AAPOR task force report.

Meilan-Vila A., Opsomer J.D., Francisco-Fernandez M., and Crujeiras R.M. (2020).

A goodness-of-fit test for regression models with spatially correlated errors.

Oliva-Aviles C., Meyer M.C., and Opsomer J.D. (2019).

Checking validity of monotone domain mean estimators.

Dohrmann S., Jones M., Kalton G., and Opsomer J. (2019).

A Review of the Address Coverage Enhancement Scheme for In-person Household Surveys.

Erciulescu A.L. and Opsomer J.D. (2019).

A model-based approach to predict employee compensation components.

Ma H., Ogawa T.K., Sminkey T.R., Breidt F.J., Lesser V.M., Opsomer J.D., Foster J.R., and Van Voorhees D.A. (2018).

Pilot surveys to improve monitoring of marine recreational fisheries in Hawaii.

Breidt F.J., Opsomer J.D., and Huang C.M. (2018).

Model-assisted survey estimation with imperfectly matched auxiliary data.

Yu H., Wang Y., Opsomer J.D., Wang P., and Ponce N. (2018).

A design-based approach to small area estimation using semiparametric generalized linear mixed models.

De Brabanter K., Cao F., Gijbels I., and Opsomer J.D. (2018).

Local polynomial regression with correlated errors in random design and unknown correlation structure.

Breidt F.J. and Opsomer J.D. (2017).

Model-assisted survey estimation with modern prediction techniques.

Hernandez-Stumpfhauser D., Breidt F.J., and Opsomer J.D. (2016).

Variational approximations for selecting hierarchical models of circular data in a small area estimation application.

Wu J., Meyer M.C., and Opsomer J.D. (2016).

Survey estimation of domain means that respect natural orderings.

Opsomer J.D., Breidt F.J., White M., and Li Y. (2016).

Successive difference replication variance estimation in two-phase sampling.

Ma H., Ogawa T.K., Breidt F.J., Lesser V.M., Opsomer J.D., Sminkey T.R., Hawkins C., Bagwill A., and Van Voorhees D.A. (2016).

Pilot surveys of shore fishing on Oahu, Hawaii.

Breidt F.J., Opsomer J.D., and Sanchez-Borrego I. (2016).

Nonparametric variance estimation under fine stratification: An alternative to collapsed strata.

Ranalli M.G., Breidt F.J., and Opsomer J.D. (2016).

Nonparametric regression methods for small area estimation.

Hernandez-Stumpfhauser D., Breidt F.J., and Opsomer J.D. (2016).

Hierarchical Bayesian small area estimation for circular data.

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