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The mecor Package

This package for R implements measurement error correction methods for measurement error in a continuous covariate or outcome in a linear model with a continuous outcome.

Installation

The package can be installed via

devtools::install_github("LindaNab/mecor", build_vignettes = TRUE)

Quick demo

library(mecor)
# load the internal covariate validation study
data("vat", package = "mecor")
head(vat)
# correct the biased exposure-outcome association
mecor(ir_ln ~ MeasError(substitute = wc, reference = vat) + age + sex + tbf, data = vat, method = "standard")

More examples

Browse the vignettes of the package for more information.

browseVignettes(package = "mecor")

References

Key reference

Nab L, van Smeden M, Keogh RH, Groenwold RHH. mecor: an R package for measurement error correction in linear models with a continuous outcome. 2021:208:106238. doi:10.1016/j.cmpb.2021.106238

References to methods implemented in the package

Bartlett JW, Stavola DBL, Frost C. Linear mixed models for replication data to efficiently allow for covariate measurement error. Statistics in Medicine. 2009:28(25):3158–3178. doi:10.1002/sim.3713
Buonaccorsi JP. Measurement error: Models, methods, and applications. 2010. Chapman & Hall/CRC, Boca Raton.
Carroll RJ, Ruppert D, Stefanski LA, Crainiceanu CM. Measurement error in non-linear models: A modern perspective. 2006, 2nd edition. Chapman & Hall/CRC, Boca Raton.
Keogh RH, Carroll RJ, Tooze JA, Kirkpatrick SI, Freedman LS. Statistical issues related to dietary intake as the response variable in intervention trials. Statistics in Medicine. 2016:35(25):4493–4508. doi:10.1002/sim.7011
Keogh RH, White IR. A toolkit for measurement error correction, with a focus on nutritional epidemiology. Statistics in Medicine 2014:33(12):2137–2155. doi:10.1002/sim.6095
Nab L, Groenwold RHH, Welsing PMJ, van Smeden M. Measurement error in continuous endpoints in randomised trials: Problems and solutions. Statistics in Medicine. 2019:38(27):5182-5196. doi:10.1002/sim.8359
Rosner B, Spiegelman D, Willett WC. Correction of logistic regression relative risk estimates and confidence intervals for measurement error: The case of multiple covariates measured with error. 1990:132(4):734-745. doi:10.1093/oxfordjournals.aje.a115715
Rosner B, Spiegelman D, Willett WC. Correction of logistic regression relative risk estimates and confidence intervals for random within-person measurement error. American Journal of Epidemiology. 1992:136(11):1400-1413. doi:10.1093/oxfordjournals.aje.a116453
Spiegelman D, Carroll RJ, Kipnis V. Efficient regression calibration for logistic regression in main study/internal validation study designs with an imperfect reference instrument. Statistics in Medicine. 2001:20(1):139-160. doi:10.1002/1097-0258(20010115)20:1<139::AID-SIM644>3.0.CO;2-K

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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