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
ivsacim_2.1.0.tar.gz(r-4.5-noble)ivsacim_2.1.0.tar.gz(r-4.4-noble)
ivsacim_2.1.0.tgz(r-4.4-emscripten)ivsacim_2.1.0.tgz(r-4.3-emscripten)
ivsacim.pdf |ivsacim.html✨
ivsacim/json (API)

# Install 'ivsacim' in R:
install.packages('ivsacim', repos = c('https://cran.r-universe.dev', '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 1 scripts 258 downloads 9 exports 2 dependencies

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

TargetResultLatest binary
Doc / VignettesOKFeb 17 2025
R-4.5-linux-x86_64NOTEFeb 17 2025

Exports:invalidivsacim_estIV_centerivsacimivsacim_estplot.ivsacimprint.summary.ivsacimsummary.ivsacimtreatment_statustrt_center

Dependencies:RcppRcppArmadillo