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robomit: Robustness Checks for Omitted Variable Bias

Robustness checks for omitted variable bias. The package includes robustness checks proposed by Oster (2019). robomit the estimate i) the bias-adjusted treatment correlation or effect and ii) the degree of selection on unobservables relative to observables (with respect to the treatment variable) that would be necessary to eliminate the result based on the framework by Oster (2019). Additionally, robomit offers a set of sensitivity analysis and visualization functions. See: Oster, E. 2019. <doi:10.1080/07350015.2016.1227711>.

Version: 1.0.6
Imports: plm, dplyr, ggplot2, broom, tidyr, tibble, stats
Suggests: testthat
Published: 2021-06-22
Author: Sergei Schaub ORCID iD [aut, cre], ETH Zurich [cph]
Maintainer: Sergei Schaub <seschaub at ethz.ch>
License: MIT + file LICENSE
NeedsCompilation: no
CRAN checks: robomit results

Documentation:

Reference manual: robomit.pdf

Downloads:

Package source: robomit_1.0.6.tar.gz
Windows binaries: r-devel: robomit_1.0.6.zip, r-release: robomit_1.0.6.zip, r-oldrel: robomit_1.0.6.zip
macOS binaries: r-release (arm64): robomit_1.0.6.tgz, r-oldrel (arm64): robomit_1.0.6.tgz, r-release (x86_64): robomit_1.0.6.tgz, r-oldrel (x86_64): robomit_1.0.6.tgz
Old sources: robomit archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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