Package: smoothedIPW 0.1.1

smoothedIPW: Time-Smoothed Inverse Probability Weighting for Repeatedly Measured Outcomes

Implements several methods to estimate effects of generalized time-varying treatment strategies on the mean of an outcome at one or more selected follow-up times of interest. Specifically, the package implements the time-smoothed inverse probability weighted estimators described in McGrath et al. (2025) <doi:10.48550/arXiv.2509.13971>. Outcomes may be repeatedly, non-monotonically, informatively, and sparsely measured in the data source. The package also supports settings where outcomes are truncated by death, i.e. some individuals die during follow-up which renders the outcome of interest undefined at the follow-up time of interest.

Authors:Sean McGrath [aut, cre], Takuya Kawahara [aut], Jessica Young [aut]

smoothedIPW_0.1.1.tar.gz
smoothedIPW_0.1.1.zip(r-4.7-any)smoothedIPW_0.1.1.zip(r-4.6-any)smoothedIPW_0.1.1.zip(r-4.5-any)
smoothedIPW_0.1.1.tgz(r-4.6-any)smoothedIPW_0.1.1.tgz(r-4.5-any)
smoothedIPW_0.1.1.tar.gz(r-4.7-any)smoothedIPW_0.1.1.tar.gz(r-4.6-any)
smoothedIPW_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
smoothedIPW/json (API)

# Install 'smoothedIPW' in R:
install.packages('smoothedIPW', repos = c('https://stmcg.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/stmcg/smoothedipw/issues

Datasets:

On CRAN:

Conda:

3.54 score 198 downloads 3 exports 12 dependencies

Last updated from:9f243f8597. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK119
source / vignettesOK140
linux-releaseOK141
macos-releaseOK149
macos-oldrelOK191
windows-develOK91
windows-releaseOK67
windows-oldrelOK87
wasm-releaseOK83

Exports:get_CIipwprep_data

Dependencies:clicrayondata.tablegluehmslifecyclepkgconfigprettyunitsprogressR6rlangvctrs