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]

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twoStageDesignTMLE.pdf |twoStageDesignTMLE.html✨
twoStageDesignTMLE/json (API)
NEWS

# 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.

1.30 score 259 downloads 6 exports 22 dependencies

Last updated 1 months agofrom:8939221cf9. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 07 2025
R-4.5-winOKMar 07 2025
R-4.5-macOKMar 07 2025
R-4.5-linuxOKMar 07 2025
R-4.4-winOKMar 07 2025
R-4.4-macOKMar 07 2025
R-4.4-linuxOKMar 07 2025
R-4.3-winOKMar 07 2025
R-4.3-macOKMar 07 2025

Exports:estimatePievalAugWsetVtwoStageDesignTMLENewstwoStageTMLEtwoStageTMLEmsm

Dependencies:bitopscaToolscodetoolscvAUCdata.tableforeachgamglmnetgplotsgtoolsiteratorsKernSmoothlatticeMatrixnnlsRcppRcppEigenROCRshapeSuperLearnersurvivaltmle