Estimate Gaps Under an Intervention

Provides functions to estimate gap-closing estimands: the disparities across categories (e.g. Black and white) that persists if a treatment variable (e.g. college) is equalized. The purpose is to estimate the average outcomes that units would realize if exposed to a counterfactual treatment assignment rule.

The package will enable the user to:

- Estimate treatment and outcome prediction functions with Generalized Linear Models, Generalized Additive Models, ridge regression, or random forest
- Combine those in doubly-robust estimators of gap-closing estimands
- Produce confidence intervals by the bootstrap
- Visualize the result in plots

Install from CRAN with one line: `install.packages("gapclosing")`

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To install the latest development version,

- First, install the
`devtools`

package:`if(!require(devtools)) install.packages("devtools")`

- Then, install the
`gapclosing`

package with the command`devtools::install_github("ilundberg/gapclosing")`

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To get started, see the vignette. Also see the working paper for which this package is the software implementation.

Lundberg, Ian. Forthcoming. “The gap-closing estimand: A causal approach to study interventions that close disparities across social categories.”

Sociological Methods and Research. Draft available at https://doi.org/10.31235/osf.io/gx4y3.