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RegCalib  

Regression Calibration for Measurement Error Correction
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("RegCalib", "0.1.0")



Attach the package and use:
library("RegCalib")
Maintained by
Jingyu Cui
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-08-07
Latest Update: 2026-08-07
Description:
Corrects for measurement error in continuous exposures and covariates using regression calibration methods. Provides corrected coefficients, standard errors, p-values, confidence intervals, and variance-covariance matrices for linear and generalized linear outcome models under an external validation study design. Implements the deattenuation factor method (RegCalibDF) and the substitution approach (RegCalibSub). Supports single and multiple error-prone exposures.
How to cite:
Jingyu Cui (2026). RegCalib: Regression Calibration for Measurement Error Correction. R package version 0.1.0, https://cran.r-project.org/web/packages/RegCalib. Accessed 24 Oct. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited RegCalib R package
View RegCalib citation profile
Other R packages that RegCalib depends, imports, suggests or enhances
Complete documentation for RegCalib
Functions, R codes and Examples using the RegCalib R package
Full RegCalib package functions and examples
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