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Rcope  

Tools to Cope with Endogeneity Problems
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("Rcope", "1.0.0")



Attach the package and use:
library("Rcope")
Maintained by
Anthony Obrzut
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-03-03
Latest Update: 2026-03-03
Description:
Researchers across disciplines often face biased regression model estimates due to endogenous regressors correlated with the error term. Traditional solutions require instrumental variables (IVs), which are often difficult to find and validate. This package provides flexible, alternative IV-free methods using copulas, as described in the practical guide to endogeneity correction using copulas (Yi Qian, Tony Koschmann, and Hui Xie 2025) <doi:10.1177/00222429251410844>. The current version implements the two-stage copula endogeneity correction (2sCOPE) method to fit models with continuous endogenous regressors and both continuous and discrete exogenous regressors, as described in Fan Yang, Yi Qian, and Hui Xie (2024) <doi:10.1177/00222437241296453>. Using this method, users can address regressor endogeneity problems in nonexperimental data without requiring IVs.
How to cite:
Anthony Obrzut (2026). Rcope: Tools to Cope with Endogeneity Problems. R package version 1.0.0, https://cran.r-project.org/web/packages/Rcope. Accessed 24 Oct. 2026.
Previous versions and publish date:
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Complete documentation for Rcope
Functions, R codes and Examples using the Rcope R package
Full Rcope package functions and examples
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