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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

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Version

Install

install.packages('mecor')

Monthly Downloads

179

Version

1.0.0

License

GPL-3

Issues

Pull Requests

Stars

Forks

Maintainer

Linda Nab

Last Published

December 1st, 2021

Functions in mecor (1.0.0)

MeasErrorExt

Create an External Measurement Error Object
ipwm

Weighting for Confounding and Joint Misclassification of Exposure and Outcome
MeasErrorRandom

Create a Random Measurement Error Object
sim

MeasError

Create a Measurement Error Object
mecor

mecor: a Measurement Error Correction Package
summary.mecor

Summarizing Measurement Error Correction
haemoglobin

Low-dose iron supplements haemoglobin data [internal outcome-validation study]
bloodpressure

PDAC blood pressure data [replicates study]
haemoglobin_ext

Haemoglobin external data [external outcome-validation study]
vat_ext

Visceral adipose tissue external data [external covariate-validation study]
vat

NEO visceral adipose tissue data [internal covariate-validation study]
sodium

TONE sodium data [outcome-calibration study]