Accounting for time-dependent covariates in driving simulator studies

Birsen Donmez, Lindang Boyle, John D. Lee

Research output: Contribution to journalArticlepeer-review


Driving involves multiple cognitive processes that are influenced by a dynamic external environment and internal feedback loops. These processes are typically studied in a simulator environment to capture time-dependent driver performance measures. The primary objective of this research is to show that data analysis techniques that ignore or improperly treat time-dependent covariates will lead to erroneous estimates and conclusions. This is demonstrated with a driving simulator study that was used to test whether a significant decrease in performance occurs in the presence of auditory and visual distractions. A total of 28 drivers participated in a 2 (age)× 7 (strategy) repeated measures experiment. The response variable—accelerator release time—was analysed with and without consideration of time-dependent covariates. Using the inverse headway distance as a time-dependent covariate corrected logically inconsistent results obtained when the covariate was ignored. This indicates that ignoring covariates can actually lead to inappropriate design or policy implications.

Original languageEnglish (US)
Pages (from-to)189-199
Number of pages11
JournalTheoretical Issues in Ergonomics Science
Issue number3
StatePublished - 2008


  • Accelerator release
  • Data analysis
  • Driving simulator
  • Headway distance
  • Time-dependent covariates

ASJC Scopus subject areas

  • Human Factors and Ergonomics


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