cid 84d16e12f2b0e2b4b8b51642a650449810ebfe232a00d90070b61572eac3dd30 · original · open access · via openalex
Title: pprof: Modeling, Standardization and Testing for Provider Profiling Authors: Xiaohan Liu; Lingfeng Luo; Yubo Shao; Xiangeng Fang; Wenbo Wu; Kevin He Venue: Year: 2024 Canonical: doi:10.32614/cran.package.pprof URL: https://doi.org/10.32614/cran.package.pprof Collector: openalex OA: true ABSTRACT 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) .