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'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

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 scripts 174 downloads 9 exports 2 dependencies

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

TargetResultDate
Doc / VignettesOKDec 19 2024
R-4.5-linux-x86_64NOTEDec 19 2024

Exports:invalidivsacim_estIV_centerivsacimivsacim_estplot.ivsacimprint.summary.ivsacimsummary.ivsacimtreatment_statustrt_center

Dependencies:RcppRcppArmadillo