Package: twoStageDesignTMLE 1.0

Susan Gruber

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.tar.gz
twoStageDesignTMLE_1.0.tar.gz(r-4.5-noble)twoStageDesignTMLE_1.0.tar.gz(r-4.4-noble)
twoStageDesignTMLE_1.0.tgz(r-4.4-emscripten)twoStageDesignTMLE_1.0.tgz(r-4.3-emscripten)
twoStageDesignTMLE.pdf |twoStageDesignTMLE.html
twoStageDesignTMLE/json (API)
NEWS

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

Peer review:

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

5 exports 0.09 score 22 dependencies

Last updated 12 days agofrom:e87d2870ef. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 06 2024
R-4.5-linuxOKSep 06 2024

Exports:evalAugWsetVtwoStageDesignTMLENewstwoStageTMLEtwoStageTMLEmsm

Dependencies:bitopscaToolscodetoolscvAUCdata.tableforeachgamglmnetgplotsgtoolsiteratorsKernSmoothlatticeMatrixnnlsRcppRcppEigenROCRshapeSuperLearnersurvivaltmle