Investigating the Influence of Alternative Survey Participant Recruitment Strategies on Measurement and Inference of Mobility Patterns

Details

• Creators:
  Pendyala, Ram M. ; Batur, Irfan ; Alhassan, Victor O. ; Yu, Fan
• Corporate Creators:
  Arizona State University. School of Sustainable Engineering and the Built Environment
• Corporate Contributors:
  United States. Department of Transportation. University Transportation Centers (UTC) Program ; National Center for Understanding Future Travel Behavior and Demand (TBD) ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  Consumer Preferences COVID-19 Data Analysis Demographics Households Measurement Methodology Mobility Mobility Measurement Online Panels Sample Recruitment Sampling Strategies Socioeconomic Factors Statistical Inference Statistical Sampling Survey Methods Surveys Survey Weighting Weighting

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• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report: 2024-2025
• Corporate Publisher:
  United States. Department of Transportation. University Transportation Centers (UTC) Program
• Abstract:
  There are growing concerns about the representativeness of survey data in an era of rapidly emerging and evolving technology, low response rates, and increasingly diverse and heterogeneous populations. Because of the complexities and costs associated with conducting surveys using traditional mail and phone methods, researchers and practitioners are adopting new methods to sample respondents. This project aims to provide a comprehensive assessment of the representativeness of the samples obtained from three survey sampling strategies utilized in the nationwide COVID Future Panel Survey: convenience sampling, email sampling, and online panel sampling. The three subsamples were statistically different from each other for all socio-economic and demographic variables except race, ethnicity, household size, and gender. However, these differences were ameliorated with the application of weights and the three subsamples converged to census distributions on many variables except educational attainment. Weighting was also able to reduce the differences between the subsamples for a variety of mobility variables except transit use frequency. Modeling the influence of survey sample recruitment strategy on measures of mobility shows that it is significant even after controlling for socio-economic and demographic variables in the model specification. It is likely that the survey sample recruitment strategy variable is accounting for unobserved traits such as attitudes and lifestyle preferences. It is therefore recommended to include attitudinal and lifestyle preference questions in transportation surveys so that these traits can be explicitly included in travel model specifications to enhance explanatory power and reduce bias.
• Format:
  PDF
• Funding:
  69A3552344815 ; 69A3552348320
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:9c605f016e41d695543d7bd0f4fd0d8aec3835d03d50bdc9fd2cc6a2796c70e8fdbfc16382404ff1eb3bee0774201abc8e0af7f9b2857bd54fb6af7d140362ae
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/91943/dot_91943_DS1.pdf
• File Type:
  [PDF - 527.79 KB ]