text-only page produced automatically by LIFT Text
Transcoder Skip all navigation and go to page contentSkip top navigation and go to directorate navigationSkip top navigation and go to page navigation
National Science Foundation HomeNational Science Foundation - Directorate for Social, Behavioral & Economic Sciences (SBE)
Social, Behavioral & Economic Sciences
design element
SBE Home
About SBE
Funding Opportunities
Advisory Committee
Career Opportunities
See Additional SBE Resources
View SBE Staff
SBE Organizations
SBE Office of Multidisciplinary Activities (SMA )
National Center for Science and Engineering Statistics (NCSE)
Division of Behavioral and Cognitive Sciences (BCS )
Division of Social and Economic Sciences (SES )
Proposals and Awards
Proposal and Award Policies and Procedures Guide
Proposal Preparation and Submission
bullet Grant Proposal Guide
  bullet Grants.gov Application Guide
Award and Administration
bullet Award and Administration Guide
Award Conditions
Merit Review
NSF Outreach
Policy Office Website
Additional SBE Resources
Advisory Committee Meetings
Career Opportunities
Funding Rates
Budget Excerpt
NSB Broader Impacts Website
Research on Cognition and Behavior
Research on Human Behavior in Time and Space
Research on Cooperation and Conflict
Exploring What Makes Us Human
Bringing People Into Focus: How Social, Behavioral & Economic Research Addresses National Challenges
Rebuilding the Mosaic Report
SBE Advisory Committee Web Site (for members only)

SBE 2020: Submission Detail

ID Number: 296
Title: Total Survey Error, Data Quality, and Statistical Error: Recommendations to the National Science Foundations Social, Behavioral, and Economic Sciences Directorate for 2020 Planning
Lead Author: Jans, Matthew E
Abstract: Social, behavioral, and economic research funded by NSF SBE is often interdisciplinary in nature (i.e., using multiple research methodologies). All research methodologies have strengths and weaknesses; one way to express these is through statistical error (e.g., sampling error, nonresponse error, measurement error). The Total Survey Error perspective on measurement and statistical estimation (Groves et al., 2009) accounts for most potential error sources in statistical estimates. We propose that this framework - although it provides a general road map to measurement and reporting of statistical findings - needs to incorporate other statistical and psychometric fields. This white paper briefly addresses the primary strengths and weaknesses of each approach to error and offers suggestions for evaluating a proposals approach to error. We recommend that NSF-SBE strengthen statistical error research by 1) requiring more documentation of and research into data quality and statistical error on substantive proposals, and 2) prioritizing data quality and statistical error research as a fundable research aim itself. Such research is essential because it builds on the basic components of statistical inference used by quantitative researchers, encourages stronger ties between substantive and methodological research, and provides a link among different facets of methodological and statistical research.
PDF: Jans_Matthew_296.pdf

SBE 2020 Home


Print this page
Back to Top of page