Who Stays and Who Leaves? Examining Sample-Source Effect on Attrition in a Longitudinal Panel Survey

Longitudinal panel surveys are a cornerstone of travel behavior research, enabling measurement of behavioral change over time and facilitating before-and-after studies of policy interventions. Despite their scientific value, panel surveys suffer from a well-documented challenge: attrition. When respondents exit the panel non-randomly between different waves of longitudinal surveys, the resulting stayer sample becomes biased, thereby undermining both sample size and representativeness. While prior literature has examined how individual socio-demographic characteristics influence panel retention, little attention has been paid to whether the initial recruitment channel through which respondents enter a panel survey shapes their propensity to remain across multiple waves. This gap limits the ability of transportation researchers and survey practitioners to design longitudinal studies that yield reliable, representative data. This project aims to examine whether recruitment strategy significantly influences panel survey retention, even after controlling for socio-economic, demographic, and attitudinal factors, and to identify which recruitment approach yields the highest retention rates. The study will use data from the COVID Future Survey, a three-wave nationwide longitudinal panel survey conducted between April 2020 and November 2021. Wave 1 recruited 8,385 valid respondents through three distinct channels: convenience sampling, mass email outreach, and a commercial online survey panel. Of the original sample, 22.5% responded to all three waves, 11.1% responded to Waves 1 and 2 only, and 66.4% responded only to Wave 1. The project will formulate and estimate a Generalized Heterogeneous Data Model (GHDM) that jointly treats recruitment strategy membership and panel survey retention as endogenous outcomes, accounting for correlated latent attitudinal constructs and socio-demographic characteristics. Latent constructs to be incorporated include Risk Perception, Work-from-Home Propensity, and Virtual Activity Perception, specified through exploratory and confirmatory factor analyses to capture shared unobserved heterogeneity that simultaneously influences recruitment channel membership and panel retention propensity. The insights derived from this project are expected to provide actionable guidance for transportation survey practitioners on recruitment strategy selection, improve the reliability and representativeness of longitudinal travel behavior data, and strengthen the data foundations underlying travel demand models and transportation planning decisions.

Language

• English

Project

• Status: Active
• Funding: $200,000.00
• Contract Numbers:

  69A3552344815

  69A3552348320

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  University of Texas at Austin

  Austin, TX  United States  78712
• Performing Organizations:

  Arizona State University

  660 S. College Ave
  PO Box 873005
  Tempe, Arizona  United States  85287
• Principal Investigators:

  Pendyala, Ram

• Start Date: 20260601
• Expected Completion Date: 20260531
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Attitudes; Before and after studies; Data collection; Longitudinal studies; Surveys; Travel behavior
• Subject Areas: Data and Information Technology; Safety and Human Factors; Transportation (General);

Filing Info

• Accession Number: 02001765
• Record Type: Research project
• Source Agency: Center for Understanding Future of Travel Behavior and Demand
• Contract Numbers: 69A3552344815, 69A3552348320
• Files: UTC, RIP
• Created Date: Sep 4 2026 2:56PM