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Code for a probabilistic sensitivity analysis of an unmeasured confounder

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Probabilitsic sensitivity analysis of an unmeasured confounder

What is the impact on our findings if we adjust for an unmeasured confounder?

In this project, we performed a probablistic sensitivity analysis using Monte Carlo simulations (MCS). In this paper we applied MCSs to quantify the impact of the suspected unmeasured confounding, i.e. low driving mileage, on the effect of polypharmacy 💊 and road traffic crashes (RTCs) 🚗 in older adults.

The code to perform the analysis is provided in this repo.

Read more here: Thiesmeier, R., Skyving, M., Möller, J., & Orsini, N. (2023). A probabilistic bias analysis on the magnitude of unmeasured confounding: The impact of driving mileage on road traffic crashes. Accident; analysis and prevention.

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Code for a probabilistic sensitivity analysis of an unmeasured confounder

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