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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 |
Reference manual: | pprof.pdf |
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 |
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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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