lmtp: Non-Parametric Causal Effects of Feasible Interventions Based on Modified Treatment Policies

Non-parametric estimators for casual effects based on longitudinal modified treatment policies as described in Diaz, Williams, Hoffman, and Schenck <doi:10.1080/01621459.2021.1955691>, traditional point treatment, and traditional longitudinal effects. Continuous, binary, and categorical treatments are allowed as well are censored outcomes. The treatment mechanism is estimated via a density ratio classification procedure irrespective of treatment variable type. For both continuous and binary outcomes, additive treatment effects can be calculated and relative risks and odds ratios may be calculated for binary outcomes.

Version: 1.3.3
Depends: R (≥ 2.10)
Imports: stats, nnls, cli, R6, generics, origami, future (≥ 1.17.0), progressr, data.table (≥ 1.13.0), checkmate (≥ 2.1.0), SuperLearner
Suggests: testthat (≥ 2.1.0), covr, rmarkdown, knitr, ranger, twang
Published: 2024-03-26
Author: Nicholas Williams ORCID iD [aut, cre, cph], Iván Díaz ORCID iD [aut, cph]
Maintainer: Nicholas Williams <ntwilliams.personal at gmail.com>
BugReports: https://github.com/nt-williams/lmtp/issues
License: AGPL-3
URL: https://github.com/nt-williams/lmtp
NeedsCompilation: no
Citation: lmtp citation info
Materials: README NEWS
In views: CausalInference
CRAN checks: lmtp results

Documentation:

Reference manual: lmtp.pdf

Downloads:

Package source: lmtp_1.3.3.tar.gz
Windows binaries: r-devel: lmtp_1.3.3.zip, r-release: lmtp_1.3.2.zip, r-oldrel: lmtp_1.3.3.zip
macOS binaries: r-release (arm64): lmtp_1.3.3.tgz, r-oldrel (arm64): lmtp_1.3.3.tgz, r-release (x86_64): lmtp_1.3.3.tgz
Old sources: lmtp archive

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