Evaluating the biases and sample size implications of multi-day GPS-enabled household travel surveys

Gregory D. Erhardt, Louis Rizzo

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations


This research explores biases and samples size implications of a multi-day GPS-enabled household travel survey. The bias tests show significant differences both across survey days and across the data collection method, indicating the weakness of the GPS-only approach use in a subsample of this survey. The research goes on to examine the sample size implications of collecting additional survey days. It finds that the three-day Northeast Ohio sample is equivalent to a single-day sample between 26% and 64% larger. The framework provides a viable means of corrected the repeated measurement problem, and should be repeated using an unbiased survey.

Original languageEnglish
Pages (from-to)279-290
Number of pages12
JournalTransportation Research Procedia
StatePublished - 2018
Event2017 ISCTC 11th International Conference on Transport Survey Methods - Esterel, Canada
Duration: Sep 24 2017Sep 29 2017

Bibliographical note

Funding Information:
This research was funded through the National Cooperative iH ghway Research Program (NCHRP) on Project 08-36C, Task 123: Survey Sample Size and Weighting. The full project report and associated appendices have been published by the Transportation Research Board as Research Results Digest 400 (Rizzo and Erhardt 2016). The work was completed by the authors as representatives of RAND and Westat. We thank Larry Goldstein and the NCHRP project panel for their valuable input, and the Ohio Department of Transpor tation and the Northeast Ohio Areawide Coordinating Agency (NOACA) for providing data.

Publisher Copyright:
© 2018 The Authors. Published by Elsevier Ltd.


  • GPS-Enabled Surveys
  • Multi-Day Surveys
  • Sample Size
  • Travel Demand Model

ASJC Scopus subject areas

  • Transportation


Dive into the research topics of 'Evaluating the biases and sample size implications of multi-day GPS-enabled household travel surveys'. Together they form a unique fingerprint.

Cite this