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LocalControl  

Nonparametric Methods for Generating High Quality Comparative Effectiveness Evidence
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("LocalControl", "1.1.4")



Attach the package and use:
library("LocalControl")
Maintained by
Christophe G. Lambert
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-05-16
Latest Update: 2022-05-20
Description:
Implements novel nonparametric approaches to address biases and confounding when comparing treatments or exposures in observational studies of outcomes. While designed and appropriate for use in studies involving medicine and the life sciences, the package can be used in other situations involving outcomes with multiple confounders. The package implements a family of methods for non-parametric bias correction when comparing treatments in observational studies, including survival analysis settings, where competing risks and/or censoring may be present. The approach extends to bias-corrected personalized predictions of treatment outcome differences, and analysis of heterogeneity of treatment effect-sizes across patient subgroups. For further details, please see: Lauve NR, Nelson SJ, Young SS, Obenchain RL, Lambert CG. LocalControl: An R Package for Comparative Safety and Effectiveness Research. Journal of Statistical Software. 2020. p. 1
How to cite:
Christophe G. Lambert (2017). LocalControl: Nonparametric Methods for Generating High Quality Comparative Effectiveness Evidence. R package version 1.1.4, https://cran.r-project.org/web/packages/LocalControl. Accessed 01 Feb. 2025.
Previous versions and publish date:
1.0.0 (2017-05-16 06:42), 1.0.1 (2017-06-03 08:27), 1.1.0 (2017-11-22 23:41), 1.1.1 (2018-06-02 08:59), 1.1.2.1 (2020-04-07 08:51), 1.1.2.2 (2020-11-26 10:10), 1.1.2 (2019-02-24 16:10), 1.1.3 (2022-05-20 20:00)
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