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RegCalib: Regression Calibration for Measurement Error Correction
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.
| Version: |
0.1.0 |
| Depends: |
R (≥ 3.5) |
| Imports: |
stats, dplyr, Matrix, matrixcalc |
| Suggests: |
knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2026-08-07 |
| DOI: |
10.32614/CRAN.package.RegCalib |
| Author: |
Jingyu Cui  [aut,
cre] (Affiliation: Department of Biostatistics, Yale School of
Public Health),
Wenze Tang [aut] (Affiliation: Vertex Pharmaceuticals),
Molin Wang [aut] (Affiliation: Department of Biostatistics, Department
of Epidemiology, Harvard T.H. Chan School of Public Health) |
| Maintainer: |
Jingyu Cui <jingyu.cui at yale.edu> |
| BugReports: |
https://github.com/JingyuCui639/RegCalib/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/JingyuCui639/RegCalib |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
RegCalib results |
Documentation:
Downloads:
Linking:
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https://CRAN.R-project.org/package=RegCalib
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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