A probabilistic bias analysis on the magnitude of unmeasured confounding: The impact of driving mileage on road traffic crashes
Unmeasured confounding can lead to biased interpretations of empirical findings. This paper aimed to assess the magnitude of suspected unmeasured confounding due to driving mileage and simulate the statistical power required to detect a discrepancy in the effect of polypharmacy on road traffic crashes (RTCs) among older adults. Based on Monte Carlo Simulation (MCS) approach, the authors estimated 1) the magnitude of confounding of driving mileage on the association of polypharmacy and RTCs and 2) the statistical power of to detect a discrepancy from no adjusted effect. A total of 1000 studies, each of 500000 observations, were simulated. Under the assumption of a modest adjusted exposure-outcome odds ratio of 1.35, the magnitude of confounding bias by driving mileage was estimated to be 16% higher with a statistical power of 50%. Only an adjusted odds ratio of at least 1.60 would be associated with a statistical power of about 80%. This applied probabilistic bias analysis showed that not adjusting for driving mileage as a confounder can lead to an overestimation of the effect of polypharmacy on RTCs in older adults. Even considering a large sample, small to moderate adjusted exposure effects were difficult to be detected.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/00014575
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Supplemental Notes:
- © 2023 The Author(s). Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
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Authors:
- Thiesmeier, Robert
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0000-0002-4590-5538
- Skyving, Marie
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0000-0003-4038-112X
- Möller, Jette
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0000-0001-9513-5896
- Orsini, Nicola
- Publication Date: 2023-10
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: 107144
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Serial:
- Accident Analysis & Prevention
- Volume: 191
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0001-4575
- Serial URL: http://www.sciencedirect.com/science/journal/00014575
Subject/Index Terms
- TRT Terms: Aged drivers; Crash rates; Distributions (Statistics); Drugged drivers; Statistical analysis; Trip length
- Subject Areas: Economics; Highways; Safety and Human Factors;
Filing Info
- Accession Number: 01889512
- Record Type: Publication
- Files: TRIS
- Created Date: Aug 1 2023 2:33PM