episensr

R package episensr: Basic Sensitivity Analysis of Epidemiological Results. Basic sensitivity analysis of the observed relative risks adjusting for unmeasured confounding and misclassification of the exposure/outcome, or both. It follows the bias analysis methods and examples from the book by Lash T.L, Fox M.P, and Fink A.K. ”Applying Quantitative Bias Analysis to Epidemiologic Data”, (’Springer’, 2009).

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 3 articles )

Showing results 1 to 3 of 3.
Sorted by year (citations)

  1. Liangyuan Hu, Jiayi Ji: CIMTx: An R package for causal inference with multiple treatments using observational data (2021) arXiv
  2. Greenland, Sander: Book review of: T. L. Lash et al., Applying quantitative bias analysis to epidemiologic data (2010)
  3. Lash, Timothy L.; Fox, Matthew P.; Fink, Aliza K.: Applying quantitative bias analysis to epidemiologic data (2009)