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psrwe

PS-Integrated Methods for Incorporating Real-World Evidence in Clinical Studies

v3.2-1 · Feb 18, 2026 · GPL (>= 3)

Description

High-quality real-world data can be transformed into scientific real-world evidence for regulatory and healthcare decision-making using proven analytical methods and techniques. For example, propensity score (PS) methodology can be applied to select a subset of real-world data containing patients that are similar to those in the current clinical study in terms of baseline covariates, and to stratify the selected patients together with those in the current study into more homogeneous strata. Then, statistical 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 real-world evidence analysis methods such as Wang et al. (2019) <doi:10.1080/10543406.2019.1657133>, Wang et al. (2020) <doi:10.1080/10543406.2019.1684309>, and Chen et al. (2020) <doi:10.1080/10543406.2020.1730877>.

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installed package size

  installed size is 90.2Mb
  sub-directories of 1Mb or more:
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NOTE 11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-oldrel-macos-arm64

installed package size

  installed size is 90.2Mb
  sub-directories of 1Mb or more:
    libs  89.3Mb
NOTE r-oldrel-macos-x86_64

installed package size

  installed size is 92.4Mb
  sub-directories of 1Mb or more:
    libs  91.5Mb
NOTE r-oldrel-windows-x86_64

for GNU extensions in Makefiles

GNU make is a SystemRequirements.

Dependency Network

Dependencies Reverse dependencies rstan Rcpp cowplot dplyr ggplot2 randomForest survival rstantools psrwe

Version History

new 3.2-1 Mar 9, 2026