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maic  

Matching-Adjusted Indirect Comparison
View on CRAN: Click here


Download and install maic package within the R console
Install from CRAN:
install.packages("maic")

Install from Github:
library("remotes")
install_github("cran/maic")

Install by package version:
library("remotes")
install_version("maic", "0.1.4")



Attach the package and use:
library("maic")
Maintained by
Rob Young
[Scholar Profile | Author Map]
First Published: 2020-04-30
Latest Update: 2022-04-27
Description:
A generalised workflow for generation of subject weights to be used in Matching-Adjusted Indirect Comparison (MAIC) per Signorovitch et al. (2012) , Signorovitch et al (2010) . In MAIC, unbiased comparison between outcomes of two trials is facilitated by weighting the subject-level outcomes of one trial with weights derived such that the weighted aggregate measures of the prognostic or effect modifying variables are equal to those of the sample in the comparator trial. The functions and classes included in this package wrap and abstract the process demonstrated in the UK National Institute for Health and Care Excellence Decision Support Unit (NICE DSU)'s example (Phillippo et al, (2016) [see URL]), providing a repeatable and easily specifiable workflow for producing multiple comparison variable sets against a variety of target studies, with preprocessing for a number of aggregate target forms (e.g. mean, median, domain limits).
How to cite:
Rob Young (2020). maic: Matching-Adjusted Indirect Comparison. R package version 0.1.4, https://cran.r-project.org/web/packages/maic. Accessed 10 Apr. 2025.
Previous versions and publish date:
0.1.2 (2020-04-30 21:00), 0.1.3 (2021-05-11 08:50)
Other packages that cited maic R package
View maic citation profile
Other R packages that maic depends, imports, suggests or enhances
Complete documentation for maic
Functions, R codes and Examples using the maic R package
Some associated functions: createMAICInput . maicMatching . maicWeight . reportCovariates . 
Some associated R codes: maic.R .  Full maic package functions and examples
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