Regression Calibration for Measurement Error Correction R package RegCalib version 0.1.0 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. Software Depends: R (>= 3.5) Imports: stats, dplyr, Matrix, matrixcalc Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Jingyu Cui <jingyu.cui@yale.edu> Comprehensive R Archive Network (CRAN) Jingyu Cui [aut, cre] (Affiliation: Department of Biostatistics, Yale School of Public Health, ORCID: <https://orcid.org/0000-0002-8073-1422>), Wenze Tang [aut] (Affiliation: Vertex Pharmaceuticals), Molin Wang [aut] (Affiliation: Department of Biostatistics, Department of Epidemiology, Harvard T.H. Chan School of Public Health) GPL-3 2026-08-07 application/tgz https://CRAN.R-project.org/package=RegCalib doi:10.32614/CRAN.package.RegCalib