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. .


Reference manual

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1.0.5 by Sergei Schaub, 3 months ago

Browse source code at

Authors: Sergei Schaub [aut, cre] , ETH Zurich [cph]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports plm, dplyr, ggplot2, broom, tidyr, tibble, stats

Suggests testthat

See at CRAN