crumble: Flexible and General Mediation Analysis Using Riesz Representers

Implements a modern, unified estimation strategy for common mediation estimands (natural effects, organic effects, interventional effects, and recanting twins) in combination with modified treatment policies as described in Liu, Williams, Rudolph, and Díaz (2024) <doi:10.48550/arXiv.2408.14620>. Estimation makes use of recent advancements in Riesz-learning to estimate a set of required nuisance parameters with deep learning. The result is the capability to estimate mediation effects with binary, categorical, continuous, or multivariate exposures with high-dimensional mediators and mediator-outcome confounders using machine learning.

Version:	0.1.2
Depends:	R (≥ 4.0.0)
Imports:	checkmate, Matrix, origami, torch, Rsymphony, purrr, cli, S7, data.table, coro, generics, lmtp, mlr3superlearner, progressr, ife (≥ 0.1.0)
Suggests:	testthat (≥ 3.0.0), truncnorm, mma
Published:	2024-12-02
DOI:	10.32614/CRAN.package.crumble
Author:	Nicholas Williams [aut, cre, cph], Richard Liu [ctb], Iván Díaz [aut, cph]
Maintainer:	Nicholas Williams <ntwilliams.personal at gmail.com>
License:	GPL (≥ 3)
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	crumble results

Documentation:

Reference manual:

crumble.pdf

Downloads:

Package source:	crumble_0.1.2.tar.gz
Windows binaries:	r-devel: crumble_0.1.2.zip, r-release: crumble_0.1.2.zip, r-oldrel: crumble_0.1.2.zip
macOS binaries:	r-release (arm64): crumble_0.1.2.tgz, r-oldrel (arm64): crumble_0.1.2.tgz, r-release (x86_64): crumble_0.1.2.tgz, r-oldrel (x86_64): crumble_0.1.2.tgz
Old sources:	crumble archive

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