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Survey Methods Research

The Office of Survey Methods Research (OSMR) evaluates the effectiveness of the survey methods currently used by BLS programs, investigates alternative methods to determine their appropriateness for BLS programs, and develops new methods for improving the efficiency and quality of BLS programs.

The program is organized into three parts: the Behavioral Science Research Center, the Data Science Research Center and the Mathematical Statistics Research Center.

Behavioral Science Research Center

Areas of Study:

  • Questionnaire design
  • Cognitive interviewing
  • Usability testing
  • Focus Groups
  • Nonresponse bias analysis
  • Measurement Error analysis
  • Respondent-interviewer interactions

Study Types:

  • Questionnaire design studies
  • Usability tests of computer systems
  • Human-computer interaction
  • Knowledge management
  • Respondent-interviewer interactions
  • Development of response-level data quality measures
  • Information seeking and retrieval
  • Metadata methods and practice

Data Science Research Center

Areas of Study:

  • Machine learning
  • Deep learning
  • Natural language processing
  • Entity resolution
  • Responsible AI
  • Machine learning operations

 Project Types:

  • Record linkage
  • Document classification & clustering
  • Entity recognition & text extraction
  • Data Science training & outreach
  • Best practice consultation & documentation

Mathematical Statistics Research Center

Areas of Study:

  • Sample design
  • Disclosure limitation
  • Bayesian methods
  • Variance estimation
  • Imputation
  • Time Series for seasonal adjustment
  • Non-parametric modeling
  • Visualization
  • Machine learning
  • Metadata methods & standards

Study Types:

  • Developing more efficient sample designs
  • Time series for seasonal adjustment
  • Missing data techniques
  • Evaluations of alternative estimators
  • Model-based estimation


Last Modified Date: May 15, 2023