CRAN/E | CausalMetaR

CausalMetaR

Causally Interpretable Meta-Analysis

Installation

About

Provides robust and efficient methods for estimating causal effects in a target population using a multi-source dataset, including those of Dahabreh et al. (2019) doi:10.1111/biom.13716 and Robertson et al. (2021) . The multi-source data can be a collection of trials, observational studies, or a combination of both, which have the same data structure (outcome, treatment, and covariates). The target population can be based on an internal dataset or an external dataset where only covariate information is available. The causal estimands available are average treatment effects and subgroup treatment effects.

github.com/ly129/CausalMetaR
Bug report File report

Key Metrics

Version 0.1.1
R ≥ 2.10
Published 2024-01-15 96 days ago
Needs compilation? no
License GPL (≥ 3)
CRAN checks CausalMetaR results

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Maintainer

Maintainer

Sean McGrath

sean_mcgrath@g.harvard.edu

Authors

Yi Lian

aut

Guanbo Wang

aut

Sean McGrath

aut / cre

Issa Dahabreh

aut

Material

README
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

Depends

R ≥ 2.10

Imports

glmnet
metafor
nnet
progress
SuperLearner

Suggests

testthat ≥ 3.0.0