causalsens: A Selection Bias Approach to Sensitivity Analysis for Causal Effects
Are your results teetering?

causalsens is an R package to implement the selection bias approach to sensitivity analysis for causal effects as introduced in Blackwell (2013). This approach allows researchers to evaulate the effect of unmeasured confounders on their estimated effects varying both the strength and direction of the confounding.

  • Browse the source and fork causalsens on github.
  • Read the vignette and check it out on CRAN.