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rACMEMEEV  

Multi-Variate Measurement Error Adjustment
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("rACMEMEEV", "1.0.1")



Attach the package and use:
library("rACMEMEEV")
Maintained by
Alexander Lee
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-12-13
Latest Update: 2025-12-13
Description:
A methodology to perform multivariate measurement error adjustment using external validation data. Allows users to remove the attenuating effect of measurement error by incorporating a distribution of external validation data, and allows for plotting of all resultant adjustments. Sensitivity analyses can also be run through this package to test how different ranges of validity coefficients can impact the effect of the measurement error adjustment. The methods implemented in this package are based on the work by Muoka, A., Agogo, G., Ngesa, O., Mwambi, H. (2020): <doi:10.12688/f1000research.27892.1>.
How to cite:
Alexander Lee (2025). rACMEMEEV: Multi-Variate Measurement Error Adjustment. R package version 1.0.1, https://cran.r-project.org/web/packages/rACMEMEEV. Accessed 12 Sep. 2026.
Previous versions and publish date:
(2026-07-09 06:47), 1.0.0 (2025-12-12 22:30)
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Complete documentation for rACMEMEEV
Functions, R codes and Examples using the rACMEMEEV R package
Full rACMEMEEV package functions and examples
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