Package: submax 1.1.1

Paul R. Rosenbaum

submax: Effect Modification in Observational Studies Using the Submax Method

Effect modification occurs if a treatment effect is larger or more stable in certain subgroups defined by observed covariates. The submax or subgroup-maximum method of Lee et al. (2017) <arxiv:1702.00525> does an overall test and separate tests in subgroups, correcting for multiple testing using the joint distribution.

Authors:Paul R. Rosenbaum

submax_1.1.1.tar.gz
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submax_1.1.1.tgz(r-4.4-emscripten)submax_1.1.1.tgz(r-4.3-emscripten)
submax.pdf |submax.html✨
submax/json (API)

# Install 'submax' in R:
install.packages('submax', repos = 'https://cloud.r-project.org')
Datasets:
  • Active - Physical Activity and Survival in NHANES
  • mercury - NHANES Mercury/Fish Data
  • tbmetaphase - Genetic damage from drugs used to treat TB

On CRAN:

Conda:

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

1.00 score 116 downloads 5 exports 2 dependencies

Last updated 7 years agofrom:3f1729c279. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 22 2025
R-4.5-linuxOKMar 22 2025
R-4.4-linuxOKMar 22 2025

Exports:amplifymscorevscoreseparable1fcsubmax

Dependencies:mvtnormsensitivityfull

Citation

To cite package ‘submax’ in publications use:

Rosenbaum PR (2017). submax: Effect Modification in Observational Studies Using the Submax Method. R package version 1.1.1, https://CRAN.R-project.org/package=submax.

ATTENTION: This citation information has been auto-generated from the package DESCRIPTION file and may need manual editing, see ‘help("citation")’.

Corresponding BibTeX entry: 

  @Manual{,
    title = {submax: Effect Modification in Observational Studies Using
      the Submax Method},
    author = {Paul R. Rosenbaum},
    year = {2017},
    note = {R package version 1.1.1},
    url = {https://CRAN.R-project.org/package=submax},
  }