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, and Hoffman (<arXiv:2006.01366>), 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: 0.9.0
Depends: R (≥ 2.10)
Imports: stats, nnls, cli, utils, R6, generics, origami, future (≥ 1.17.0), progressr, data.table, SuperLearner
Suggests: testthat (≥ 2.1.0), covr, rmarkdown, knitr, ranger, twang
Published: 2021-02-22
Author: Nicholas Williams ORCID iD [aut, cre, cph], Iván Díaz ORCID iD [aut, cph]
Maintainer: Nicholas Williams <niw4001 at med.cornell.edu>
License: AGPL-3
NeedsCompilation: no
Citation: lmtp citation info
Materials: README NEWS
CRAN checks: lmtp results

Downloads:

Reference manual: lmtp.pdf
Vignettes: getting-started
Package source: lmtp_0.9.0.tar.gz
Windows binaries: r-devel: lmtp_0.9.0.zip, r-release: lmtp_0.0.5.zip, r-oldrel: lmtp_0.0.5.zip
macOS binaries: r-release: lmtp_0.9.0.tgz, r-oldrel: lmtp_0.0.5.tgz
Old sources: lmtp archive

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