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)
<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>.
| Version: |
3.1 |
| Depends: |
methods, R (≥ 4.0), rstan (≥ 2.19.3), Rcpp (≥ 1.0.5) |
| Imports: |
parallel (≥ 3.2), cowplot (≥ 1.0.0), dplyr (≥ 0.8.5), ggplot2 (≥ 3.3.2), randomForest (≥ 4.6-14), survival, rstantools (≥ 2.1.1) |
| LinkingTo: |
BH (≥ 1.72.0-3), rstan (≥ 2.19.3), Rcpp (≥ 1.0.5), RcppEigen (≥ 0.3.3.7.0), StanHeaders (≥ 2.21.0-5), RcppParallel (≥ 5.0.2) |
| Suggests: |
knitr, rmarkdown |
| Published: |
2022-03-01 |
| Author: |
Chenguang Wang [aut, cre],
Trustees of Columbia University [cph] (tools/make_cpp.R,
R/stanmodels.R),
Wei-Chen Chen [aut] |
| Maintainer: |
Chenguang Wang <chenguang.wang.0517 at gmail.com> |
| BugReports: |
https://github.com/olssol/psrwe/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/olssol/psrwe |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make |
| Materials: |
NEWS |
| CRAN checks: |
psrwe results |