Package: twoStageDesignTMLE 1.0.1.2

twoStageDesignTMLE: Targeted Maximum Likelihood Estimation for Two-Stage Study Design

An inverse probability of censoring weighted (IPCW) targeted maximum likelihood estimator (TMLE) for evaluating a marginal point treatment effect from data where some variables were collected on only a subset of participants using a two-stage design (or marginal mean outcome for a single arm study). A TMLE for conditional parameters defined by a marginal structural model (MSM) is also available.

Authors:Susan Gruber [aut, cre], Mark van der Laan [aut]

twoStageDesignTMLE_1.0.1.2.tar.gz
twoStageDesignTMLE_1.0.1.2.zip(r-4.7-any)twoStageDesignTMLE_1.0.1.2.zip(r-4.6-any)twoStageDesignTMLE_1.0.1.2.zip(r-4.5-any)
twoStageDesignTMLE_1.0.1.2.tgz(r-4.6-any)twoStageDesignTMLE_1.0.1.2.tgz(r-4.5-any)
twoStageDesignTMLE_1.0.1.2.tar.gz(r-4.7-any)twoStageDesignTMLE_1.0.1.2.tar.gz(r-4.6-any)
twoStageDesignTMLE_1.0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
twoStageDesignTMLE/json (API)

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

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 197 downloads 6 exports 23 dependencies

Last updated from:8939221cf9. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK110
source / vignettesOK147
linux-releaseOK102
macos-releaseOK197
macos-oldrelOK164
windows-develOK101
windows-releaseOK82
windows-oldrelOK76
wasm-releaseOK79

Exports:estimatePievalAugWsetVtwoStageDesignTMLENewstwoStageTMLEtwoStageTMLEmsm

Dependencies:bitopscaToolscodetoolscvAUCdata.tableforeachgamglmnetgplotsgtoolsiteratorsKernSmoothlatticeMatrixnnlsRcppRcppEigenrlangROCRshapeSuperLearnersurvivaltmle