CRAN/E | lmtp

lmtp

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

Installation

About

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.

Citation lmtp citation info
github.com/nt-williams/lmtp
Bug report File report

Key Metrics

Version 1.3.3
R ≥ 2.10
Published 2024-03-26 25 days ago
Needs compilation? no
License AGPL-3
CRAN checks lmtp results

Downloads

Yesterday 13 0%
Last 7 days 89 -23%
Last 30 days 544 +49%
Last 90 days 1.460 +37%
Last 365 days 4.774 +18%

Maintainer

Maintainer

Nicholas Williams

ntwilliams.personal@gmail.com

Authors

Nicholas Williams

aut / cre / cph

Iván Díaz

aut / cph

Material

README
NEWS
Reference manual
Package source

In Views

CausalInference

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

lmtp archive

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