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CausalMetaR
View on CRAN: Click
here
Download and install CausalMetaR package within the R console
Install from CRAN:
install.packages("CausalMetaR")
Install from Github:
library("remotes")
install_github("cran/CausalMetaR")
Install by package version:
library("remotes")
install_version("CausalMetaR", "0.1.2")
Attach the package and use:
library("CausalMetaR")
Maintained by
Sean McGrath
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.CausalMetaR . https://github.com/ly129/CausalMetaR/issues . https://github.com/ly129/CausalMetaR . CausalMetaR results . CausalMetaR.pdf . CausalMetaR_0.1.2.tar.gz . CausalMetaR_0.1.2.zip . CausalMetaR_0.1.2.zip . CausalMetaR_0.1.2.zip . CausalMetaR_0.1.2.tgz . CausalMetaR_0.1.2.tgz . CausalMetaR_0.1.2.tgz . CausalMetaR_0.1.2.tgz . CausalMetaR_0.1.2.tgz . CausalMetaR_0.1.2.tgz . CausalMetaR archive . https://CRAN.R-project.org/package=CausalMetaR .
First Published: 2024-01-15
Latest Update: 2024-01-15
Description:
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) 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.
How to cite:
Sean McGrath (2024). CausalMetaR: Causally Interpretable Meta-Analysis. R package version 0.1.2, https://cran.r-project.org/web/packages/CausalMetaR. Accessed 02 Apr. 2025.
Previous versions and publish date:
0.1.1 (2024-01-15 17:30)
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