Sharon Lohr, Ph.D.

Nonresident Senior Fellow

Sharon Lohr, Ph.D., is Professor Emerita at Arizona State University. She was a Vice President and senior statistician at Westat from 2012 to 2017, and prior to that was Dean’s Distinguished Professor of Statistics at Arizona State University.

Dr. Lohr is the author of the book Sampling: Design and Analysis and has published numerous articles in leading journals on survey sampling, hierarchical models, small area estimation, missing data, and design of experiments. She is a Fellow of the American Statistical Association, an elected member of the International Statistical Institute, the inaugural recipient of the Gertrude M. Cox Statistics Award for contributions to the practice of statistics, and the 2009 recipient of the Morris Hansen Lecture Award. In 2014, she was selected to present the Deming Lecture at the Joint Statistical Meetings. In 2016, she was selected to present the Distinguished Lecture in the Joint Program for Survey Methodology.

In recognition of her contributions to the field, Dr. Lohr has been named a Westat nonresident Senior Statistical Fellow and serves on the Statistical Fellows Committee, which provides consultation on important survey statistics issues and addresses recent advances in applied statistics.


Ph.D., Statistics, University of Wisconsin-Madison
B.S., Mathematics, Calvin College

Areas of Expertise

Selected Publications

Tourangeau R., Brick J.M., Lohr S., Li J. (2017).

Adaptive and responsive survey designs: A review and assessment.

Lohr S., Raghunathan T.E. (2017).

Combining survey data with other data sources.

Hyland A., Ambrose B.K., Conway K.P., Borek N., Lambert E., Carusi C., Taylor K., Crosse S.B., Fong G.T., Cummings K.M., Abrams D., Pierce J.P., Sargent J., Messer K., Bansal-Travers M., Niaura R., Vallone D., Hammond D., Hilmi N., Kwan J., Piesse A., Kalton G., Lohr S., Pharris-Ciurej N., Castleman V., Green V.R., Tessman G., Kaufman A., Lawrence C., van Bemmel D.M., Kimmel H.L., Blount B., Yang L., O'Brien B., Tworek C., Alberding D., Hull L.C., Cheng Y.C., Maklan D., Backinger C.L., Compton W.M. (2017).

Design and methods of the Population Assessment of Tobacco and Health (PATH) Study.

Riddles M.K., Lohr S., Brick J.M., Langetieg P.T., Payne J.M., Plumley A.H. (2017).

Handling respondent rounding of wages using the IRS and CPS matched dataset.

Lohr S., Brick J.M. (2017).

Roosevelt predicted to win: Revisiting the 1936 Literary Digest Poll.

Piesse A., Lohr S. (2016).

Sample design for longitudinal multiphase samples with misclassification.

Lohr S., Riddles M.K., Morganstein D. (2016).

Tests for evaluating nonresponse bias in surveys.

Lohr S., Zhu X. (2015).

Randomized sequential individual assignment in social experiments: Evaluating the design options prospectively.

Lohr S. (2015).

Red beads and profound knowledge: Deming and quality of education.

Lohr S., Hsu V., DeMatteis J.M. (2015).

Using classification and regression trees to model survey nonresponse.

Lohr S., Brick J.M. (2014).

Allocation for dual frame telephone surveys with nonresponse.

Lohr S., Schochet P.Z. (2014).

Analyzing data from experiments in which the treatment groups have different hierarchical structures.

Cecere W., Jiao R., Rozsi M., Severynse J.A., Lohr S., Green J. (2014).

Composite measure of size evaluation and primary sampling unit formation for NHTSA’s Redesign of the National Automotive Sampling System.

Karl A.T., Yang Y., Lohr S. (2014).

Computation of maximum likelihood estimates for multiresponse generalized linear mixed models with non-nested, correlated random effects.

Rozsi M., Cecere W., Lohr S., Green J. (2014).

Creating a flexible and scalable PSU sample for NHTSA's redesign of the National Automotive Sampling System.

Lohr S. (2014).

Design effects for a regression slope in a cluster sample.

Jiao R., Sugawara Y., Rozsi M., Lohr S., Green J., Cecere W. (2014).

Estimating population and design parameters for NHTSA's new National Automotive Sampling System (NASS).

Lohr S., Schochet P., Sanders E. (2014).

Partially nested randomized controlled trials in education research: A guide to design and analysis.

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