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robomit  

Robustness Checks for Omitted Variable Bias
View on CRAN: Click here


Download and install robomit package within the R console
Install from CRAN:
install.packages("robomit")

Install from Github:
library("remotes")
install_github("cran/robomit")

Install by package version:
library("remotes")
install_version("robomit", "1.0.6")



Attach the package and use:
library("robomit")
Maintained by
Sergei Schaub
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-09-15
Latest Update: 2021-06-22
Description:
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>.
How to cite:
Sergei Schaub (2020). robomit: Robustness Checks for Omitted Variable Bias. R package version 1.0.6, https://cran.r-project.org/web/packages/robomit
Previous versions and publish date:
1.0.3 (2020-09-15 11:30), 1.0.5 (2021-01-25 17:00)
Other packages that cited robomit R package
View robomit citation profile
Other R packages that robomit depends, imports, suggests or enhances
Functions, R codes and Examples using the robomit R package
Some associated functions: o_beta . o_beta_boot . o_beta_boot_inf . o_beta_boot_viz . o_beta_rsq . o_beta_rsq_viz . o_delta . o_delta_boot . o_delta_boot_inf . o_delta_boot_viz . o_delta_rsq . o_delta_rsq_viz . 
Some associated R codes: robomit_functions.R .  Full robomit package functions and examples
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