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DESCRIPTION
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DESCRIPTION
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Package: medshift
Title: Causal mediation analysis for stochastic interventions
Version: 0.1.4
Authors@R: c(
person("Nima", "Hejazi", email = "[email protected]",
role = c("aut", "cre", "cph"),
comment = c(ORCID = "0000-0002-7127-2789")),
person("Iván", "Díaz", email = "[email protected]",
role = c("aut"),
comment = c(ORCID = "0000-0001-9056-2047")),
person("Mark", "van der Laan", email = "[email protected]",
role = c("ctb", "ths"),
comment = c(ORCID = "0000-0003-1432-5511")),
person("Jeremy", "Coyle", email = "[email protected]",
role = "ctb",
comment = c(ORCID = "0000-0002-9874-6649"))
)
Maintainer: Nima Hejazi <[email protected]>
Description: Estimators of a parameter arising in the decomposition of the
population intervention (in)direct effect of stochastic interventions in
causal mediation analysis, including efficient one-step, targeted minimum
loss (TML), re-weighting (IPW), and substitution estimators. The parameter
estimated constitutes a part of each of the population intervention
(in)direct effects. These estimators may be used in assessing population
intervention (in)direct effects under stochastic treatment regimes,
including incremental propensity score interventions and modified treatment
policies. The methodology was first discussed by I Díaz and NS Hejazi
(2020) <doi:10.1111/rssb.12362>.
Depends: R (>= 3.2.0)
Imports:
R6,
uuid,
stats,
methods,
dplyr,
tidyr,
tibble,
data.table,
assertthat,
origami,
sl3,
tmle3
Suggests:
testthat,
knitr,
rmarkdown,
stringr,
Rsolnp,
nnls,
speedglm,
glmnet,
hal9001,
xgboost,
ranger,
mma
Remotes:
github::tlverse/sl3@master,
github::tlverse/tmle3@master
License: MIT + file LICENSE
URL: https://github.com/nhejazi/medshift
BugReports: https://github.com/nhejazi/medshift/issues
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.1.0
Roxygen: list(markdown = TRUE, old_usage = TRUE, r6 = FALSE)