An official website of the United States government
United States Department of Labor
United States Department of Labor
The .gov means it's official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information,
make sure you're on a federal government site.
The site is secure.
The
https:// ensures that you are connecting to the official website and that any
information you provide is encrypted and transmitted securely.
Office of Survey Methods Research
SHARE ON:
ASA/NSF/BLS Senior Research Fellow Program
| Researcher | University | Year | Title |
|---|---|---|---|
|
Carol Hert |
Syracuse University | 2000 | Understanding and Modeling Metadata Use by BLS Survey Methodologists |
|
Sarah Nusser |
Iowa State University | 2002 | Strategies for Improving Abilities to Use Digital Maps |
|
Jean Opsomer |
Iowa State University | 2003 | Semiparametric Estimation for the Current Employment Statistics Survey |
|
Lijian Yang |
Michigan State University | 2003 | Non-and Semi-parametric Analysis of Multivariate Seasonal Time Series Data |
|
Iddo Gal |
University of Haifa | 2004 | Improving Dissemination Efforts at BLS: Understanding Statistics in Tables and Graphs |
|
Partha Lahiri |
University of Nebraska-Lincoln | 2004 | Model-based Estimation using Current Employment Statistics Database |
|
Scott Holan |
University of Missouri- Columbia | 2006 | Explore Diagnostics for Model-based Seasonal Adjustment in both the time and Spectral Domains |
|
Robert Drago |
Penn State | 2007 | Simultaneous Activities in the American Time Use Survey: An Exploratory Analysis |
|
Lily Wang |
University of Georgia | 2010 | Flexible and Robust Estimation for Complex Survey Sampling |
|
Kimberly Sellers |
Georgetown | 2010 | Advances with the Conway-Maxwell-Poisson Distribution |
|
Nicholas Horton |
Amherst College | 2011 | Use of Auxiliary Data and Sensitivity Analyses for Efficient Design and Analysis of Employment and Establishment Studies with Missing Observations |
|
Ting Yan |
University of Michigan | 2013 | Response Burden: What Predicts It and What is its Impact on Response Quality? |
|
Mary Meyer |
Colorado State University | 2013 | Multiple Constrained Regression with Applications to Sparse Data with Ordinal Predictors |
|
Wei-Yin Loh |
University of Wisconsin | 2014 | Classification and Regression Tree Methods for Sample Survey Data |
|
Ana Aizcorbe |
Virginia Tech | 2015 | How well does the MarketScan Claims Data Represent Commercially-insured Individuals in the US: Implications for Price Indexes |
|
Sara Wuellner |
Washington State Department of Labor and Industries | 2015 | Employer-based occupational injury and illness recordkeeping practices, data from four states |
|
Michael Handel |
Northeastern University | 2016 | Understanding Job Requirements, Technology, and their Relationships to Employment and Wages: Levels and Trends |
|
Kelly McConville |
Swarthmore College | 2016 | Support Vector Machines as an Imputation Model |
|
Jingchen (Monika) Hu |
Vassar College | 2017 | Synthetic Consumer Expenditure Survey Data at BLS |
|
Phillip S. Kott |
RTI International | 2018 | Calibration Weighting for the Occupational Requirements Survey |
|
Stephanie Eckman |
RTI International | 2018 | Investigating and Reducing Motivated Misreporting in the Consumer Expenditure Interview Survey |
|
Roee Gutman |
Brown University | 2022 | Improvements in Implementations and Analysis of Record Linkage Algorithms |
|
Wenjiang Fu |
University of Houston | 2022 | Combining Multiple Survey Data to Efficiently Model Consumer Expenditures |
Last Modified Date: October 4, 2022