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pprof: Modeling, Standardization and Testing for Provider Profiling

Implements linear and generalized linear models for provider profiling, incorporating both fixed and random effects. For large-scale providers, the linear profiled-based method and the SerBIN method for binary data reduce the computational burden. Provides post-modeling features, such as indirect and direct standardization measures, hypothesis testing, confidence intervals, and post-estimation visualization. For more information, see Wu et al. (2022) <doi:10.1002/sim.9387>.

Version: 1.0.1
Depends: R (≥ 4.1.0)
Imports: Rcpp, RcppParallel, stats, caret, olsrr, pROC, poibin, dplyr, ggplot2, Matrix, lme4, magrittr, scales, tibble, rlang
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-12-12
DOI: 10.32614/CRAN.package.pprof
Author: Xiaohan Liu [aut, cre], Lingfeng Luo [aut], Yubo Shao [aut], Xiangeng Fang [aut], Wenbo Wu [aut], Kevin He [aut]
Maintainer: Xiaohan Liu <xhliuu at umich.edu>
License: MIT + file LICENSE
URL: https://github.com/UM-KevinHe/pprof
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README
CRAN checks: pprof results

Documentation:

Reference manual: pprof.pdf

Downloads:

Package source: pprof_1.0.1.tar.gz
Windows binaries: r-devel: pprof_1.0.1.zip, r-release: not available, r-oldrel: pprof_1.0.1.zip
macOS binaries: r-release (arm64): pprof_1.0.1.tgz, r-oldrel (arm64): pprof_1.0.1.tgz, r-release (x86_64): pprof_1.0.1.tgz, r-oldrel (x86_64): pprof_1.0.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=pprof to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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