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Statistical Sciences

Survey Statistics, Survey Methodology & Statistical Analysis

Westat leads the field in innovative and robust statistical and methodological research to meet the challenging needs of our clients. We create and implement solutions by harnessing the power of artificial intelligence (AI), machine learning (ML), natural language processing (NLP), data analytics, data integration, survey statistics, and survey methods. Our goal is to deliver the highest quality research and approaches.

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See how we can answer questions like...

How can text data be quickly and accurately processed?

How do you effectively work with a vast amount of data for a large K-12 survey?

What’s the best method for estimating employee compensation across job types?

How do researchers account for underreporting in surveys?

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Statistical Sciences Leadership

Jeri Mulrow
Jeri Mulrow
Vice President, Statistics and Evaluation Sciences Director

Meet our Experts

12

ASA Fellows

80+

Staff

160

Recent Publications

News

Statistical Sciences

New Variance Estimation Method Proposed for Calibrating to Random Control Totals

Data Collection & Survey Research

Can an Alternative Weighting Method Adapt for Differences in Multimode Collection?

Data Collection & Survey Research

2021 Federal Committee on Statistical Methodology (FCSM) Meeting Serves as Key Forum

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Publications

Erciulescu A.L., Opsomer J.D., and Breidt F.J. (2021).

A bridging model to reconcile statistics based on data from multiple surveys.

Annals of Applied Statistics, 15(2), 1068-1079.
Source | DOI
Fay R.E. (2021).

Constructing and disseminating small area estimates from the National Crime Victimization Survey, 2007–2018.

Washington, DC: Office of Justice Programs, Bureau of Justice Statistics, U.S. Department of Justice.
Source (PDF)
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.

Test, 29, 728-749.
DOI

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