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psrwe  

PS-Integrated Methods for Incorporating RWE in Clinical Studies
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("psrwe", "3.1")



Attach the package and use:
library("psrwe")
Maintained by
Chenguang Wang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-09-08
Latest Update: 2023-09-28
Description:
High-quality real-world data can be transformed into scientific real-world evidence (RWE) for regulatory and healthcare decision-making using proven analytical methods and techniques. For example, propensity score (PS) methodology can be applied to pre-select a subset of real-world data containing patients that are similar to those in the current clinical study in terms of covariates, and to stratify the selected patients together with those in the current study into more homogeneous strata. Then, methods such as the power prior approach or composite likelihood approach can be applied in each stratum to draw inference for the parameters of interest. This package provides functions that implement the PS-integrated RWE analysis methods proposed in Wang et al. (2019) , Wang et al. (2020) and Chen et al. (2020) .
How to cite:
Chenguang Wang (2020). psrwe: PS-Integrated Methods for Incorporating RWE in Clinical Studies. R package version 3.1, https://cran.r-project.org/web/packages/psrwe. Accessed 21 Dec. 2024.
Previous versions and publish date:
1.2 (2020-09-08 10:20), 1.3 (2021-04-16 08:10), 3.0 (2022-01-07 17:52), 3.1 (2022-03-01 16:20)
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