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concrete
View on CRAN: Click
here
Download and install concrete package within the R console
Install from CRAN:
install.packages("concrete")
Install from Github:
library("remotes")
install_github("cran/concrete")
Install by package version:
library("remotes")
install_version("concrete", "1.0.5")
Attach the package and use:
library("concrete")
Maintained by
David Chen
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-09-10
Latest Update: 2023-09-10
Description:
One-step continuous-time Targeted Minimum Loss-Based Estimation (TMLE) for outcome-specific absolute risk estimands in right-censored survival settings with or without competing risks, implementing the methodology described in Rytgaard et al. (2023) and Rytgaard and van der Laan (2023) . Currently 'concrete' can be used to estimate the effects of static or dynamic interventions on binary treatments given at baseline, cross-validated initial estimation of treatment propensity is done using the 'SuperLearner' package, and initial estimation of conditional hazards is done using ensembles of Cox regressions from the 'survival' package or Coxnet from the 'glmnet' package.
How to cite:
David Chen (2023). concrete: Continuous-Time Competing Risks Estimation using Targeted
Minimum Loss-Based Estimation (TMLE). R package version 1.0.5, https://cran.r-project.org/web/packages/concrete
Previous versions and publish date:
1.0.5 (2023-09-10 18:50)
Other packages that cited concrete R package
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imports, suggests or enhances
Functions, R codes and Examples using
the concrete R package
Some associated functions: concrete-package . doConcrete . doTmleUpdate . formatArguments . getEIC . getHazFit . getInitialEstimate . getOutput . getPropScore .
Some associated R codes: RcppExports.R . doConcrete.R . doTmleUpdate.R . formatArguments.R . getEIC.R . getHazEstimate.R . getInitialEstimate.R . getOutput.R . getPropScore.R . Full concrete package functions and examples
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