sensemakr: Sensitivity Analysis Tools for OLS (Stata)

sensemakr for Stata 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).

Related Packages

Download the R package here: https://github.com/carloscinelli/sensemakr/
Download the Python package here: https://github.com/nlapier2/PySensemakr
Check out the Robustness Value Shiny App at: https://carloscinelli.shinyapps.io/robustness_value/

Installation

SSC

To install from SSC, run:

ssc install sensemakr, all replace

Development version

To install the current development version on github, run:

net install sensemakr, all replace force from("https://raw.githubusercontent.com/resonance1/sensemakr-stata/master/")

Citation

Please use the following citations:

Basic Usage

// Load dataset
use darfur.dta, clear

// Run sensitivity analysis, using female as a benchmark covariate:
sensemakr peacefactor directlyharmed age farmer_dar herder_dar pastvoted hhsize_darfur female ///
i.village_factor, treat(directlyharmed) benchmark(female)

// Generate a contour plot
sensemakr peacefactor directlyharmed age farmer_dar herder_dar pastvoted hhsize_darfur female ///
i.village_factor, treat(directlyharmed) benchmark(female) contourplot

// Generate a t-contour plot
sensemakr peacefactor directlyharmed age farmer_dar herder_dar pastvoted hhsize_darfur female ///
i.village_factor, treat(directlyharmed) benchmark(female) tcontourplot

// Generate an extreme scenario plot
sensemakr peacefactor directlyharmed age farmer_dar herder_dar pastvoted hhsize_darfur female ///
i.village_factor, treat(directlyharmed) benchmark(female) extremeplot