Probabilistic Bias Analysis
Monte Carlo sensitivity analysis for misclassification, selection, and confounding bias
Based on episensr::probsensMonte Carlo Simulation
2×2 Contingency Table
Enter observed cell counts
Exposed
Unexposed
Cases
Controls
Bias Type & Parameters
Select bias type and specify probability distributions
P(test+ | truly exposed)
P(test- | truly unexposed)
Simulation Settings
Enter data and click “Run Monte Carlo” to see results
Method
Probabilistic sensitivity analysis samples bias parameters from specified distributions and recalculates the effect estimate for each iteration.
Based on methods from Lash TL, Fox MP, MacLehose RF (2021). Applying Quantitative Bias Analysis to Epidemiologic Data. Springer.
Learn More About Probabilistic Bias Analysis
Understand how to specify prior distributions for bias parameters and interpret Monte Carlo simulation results for quantitative bias analysis.