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CausalMetaR  

Causally Interpretable Meta-Analysis
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", "0.1.3")



Attach the package and use:
library("CausalMetaR")
Maintained by
Sean McGrath
[Scholar Profile | Author Map]
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 0.1.3, https://cran.r-project.org/web/packages/CausalMetaR. Accessed 03 May. 2025.
Previous versions and publish date:
0.1.1 (2024-01-15 17:30), 0.1.2 (2024-06-04 15:40)
Other packages that cited CausalMetaR R package
View CausalMetaR citation profile
Other R packages that CausalMetaR depends, imports, suggests or enhances
Complete documentation for CausalMetaR
Functions, R codes and Examples using the CausalMetaR R package
Full CausalMetaR package functions and examples
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