Package: psrwe
Title: PS-Integrated Methods for Incorporating RWE in Clinical Studies
Version: 3.1
Authors@R: c(
    person(given = "Chenguang", family = "Wang",
           email = "chenguang.wang.0517@gmail.com",
           role = c("aut", "cre")),
    person(given = "Trustees of Columbia University",
           role = "cph",
           comment = "tools/make_cpp.R, R/stanmodels.R"),
    person(given = "Wei-Chen", family = "Chen",
           role = c("aut")))
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)
    <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>.
Depends: methods, R (>= 4.0), rstan (>= 2.19.3), Rcpp (>= 1.0.5)
License: GPL (>= 3)
URL: https://github.com/olssol/psrwe
BugReports: https://github.com/olssol/psrwe/issues
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)
RcppModules: stan_fit4powerp_mod, stan_fit4powerps_mod,
        stan_fit4powerpsbinary_mod, stan_fit4prior_mod
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)
Suggests: knitr, rmarkdown
Encoding: UTF-8
LazyData: true
ByteCompile: true
SystemRequirements: GNU make
NeedsCompilation: yes
RoxygenNote: 7.1.2
VignetteBuilder: knitr
Packaged: 2022-02-28 23:21:10 UTC; chenguang.wang
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@gmail.com>
Repository: CRAN
Date/Publication: 2022-03-01 15:20:02 UTC
Built: R 4.1.3; x86_64-w64-mingw32; 2023-04-17 18:43:31 UTC; windows
Archs: x64
