Package: ivsacim 2.1.0

Andrew Ying

ivsacim: Structural Additive Cumulative Intensity Models with IV

An instrumental variable estimator under structural cumulative additive intensity model is fitted, that leverages initial randomization as the IV. The estimator can be used to fit an additive hazards model under time to event data which handles treatment switching (treatment crossover) correctly. We also provide a consistent variance estimate.

Authors:Andrew Ying

ivsacim_2.1.0.tar.gz
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ivsacim.pdf |ivsacim.html✨
ivsacim/json (API)

# Install 'ivsacim' in R:
install.packages('ivsacim', repos = 'https://cloud.r-project.org')
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

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

openblascpp

1.00 score 1 stars 215 downloads 9 exports 2 dependencies

Last updated 3 years agofrom:ad7d169809. Checks:1 OK, 2 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 19 2025
R-4.5-linux-x86_64NOTEMar 19 2025
R-4.4-linux-x86_64NOTEMar 19 2025

Exports:invalidivsacim_estIV_centerivsacimivsacim_estplot.ivsacimprint.summary.ivsacimsummary.ivsacimtreatment_statustrt_center

Dependencies:RcppRcppArmadillo

Citation

To cite package ‘ivsacim’ in publications use:

Ying A (2022). ivsacim: Structural Additive Cumulative Intensity Models with IV. R package version 2.1.0, https://CRAN.R-project.org/package=ivsacim.

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 = {ivsacim: Structural Additive Cumulative Intensity Models
      with IV},
    author = {Andrew Ying},
    year = {2022},
    note = {R package version 2.1.0},
    url = {https://CRAN.R-project.org/package=ivsacim},
  }