Sensitivity Analysis Tools for Regression Models
Add bounds to contour plot of omitted variable bias
Bias-adjusted critical values
Bias-adjusted estimates, standard-errors, t-values and confidence inte...
Partial R2 of groups of covariates in a linear regression model
Helper function for extracting model statistics
Bounds on the strength of unobserved confounders using observed covari...
Contour plots of omitted variable bias
Extreme scenarios plots of omitted variable bias
Computes the partial R2 and partial (Cohen's) f2
Sensitivity analysis plots for sensemakr
Sensitivity analysis print and summary methods for sensemakr
Creates orthogonal residuals
Computes the (extreme) robustness value
Sensemakr: extending omitted variable bias
Sensitivity analysis to unobserved confounders
Sensitivity statistics for regression coefficients
Implements a suite of sensitivity analysis tools that extends the traditional omitted variable bias framework and makes it easier to understand the impact of omitted variables in regression models, as discussed in Cinelli, C. and Hazlett, C. (2020), "Making Sense of Sensitivity: Extending Omitted Variable Bias." Journal of the Royal Statistical Society, Series B (Statistical Methodology) <doi:10.1111/rssb.12348>.
Useful links