Package: augSIMEX 3.7.4

Qihuang Zhang

augSIMEX: Analysis of Data with Mixed Measurement Error and Misclassification in Covariates

Implementation of the augmented Simulation-Extrapolation (SIMEX) algorithm proposed by Yi et al. (2015) <doi:10.1080/01621459.2014.922777> for analyzing the data with mixed measurement error and misclassification. The main function provides a similar summary output as that of glm() function. Both parametric and empirical SIMEX are considered in the package.

Authors:Qihuang Zhang <qihuang.zhang@uwaterloo.ca>, Grace Y. Yi <yyi@uwaterloo.ca>

augSIMEX_3.7.4.tar.gz
augSIMEX_3.7.4.tar.gz(r-4.5-noble)augSIMEX_3.7.4.tar.gz(r-4.4-noble)
augSIMEX_3.7.4.tgz(r-4.4-emscripten)augSIMEX_3.7.4.tgz(r-4.3-emscripten)
augSIMEX.pdf |augSIMEX.html✨
augSIMEX/json (API)

# Install 'augSIMEX' in R:
install.packages('augSIMEX', repos = 'https://cloud.r-project.org')
Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • GeneRepeat - Example data for univariate error-prone covariates in repeated measurements case
  • GeneUni - Example of genetic data for univariate error-prone covariates
  • ToyMult - Toy example data for multivariate error-prone covariates
  • ToyRepeat - Toy example data for univariate error-prone covariates in repeated measurements case
  • ToyUni - Toy example data for univariate error-prone covariates

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

1.00 score 354 downloads 9 exports 4 dependencies

Last updated 5 years agofrom:e990a81bdb. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 14 2025
R-4.5-linux-x86_64OKMar 14 2025
R-4.4-linux-x86_64OKMar 14 2025

Exports:augSIMEXcoef.augSIMEXglmscorelogLik.augSIMEXplot.augSIMEXpredict.augSIMEXresiduals.augSIMEXsummary.augSIMEXvcov.augSIMEX

Dependencies:FormulaMASSnleqslvRcpp

Citation

To cite the 'augSIMEX' package in publications use:

Zhang Q, Yi G Y. R package for analysis of data with mixed measurement error and misclassification in covariates: augSIMEX[J]. Journal of Statistical Computation and Simulation, 2019: 1-23.

Corresponding BibTeX entry: 

  @Article{,
    title = {R package for analysis of data with mixed measurement
      error and misclassification in covariates: augSIMEX},
    author = {Qihuang Zhang and Grace Y Yi},
    journal = {Journal of Statistical Computation and Simulation},
    year = {2019},
    pages = {1--23},
    publisher = {Taylor & Francis},
  }