Crandore Hub

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>.

Versions across snapshots

VersionRepositoryFileSize
1.0.3 rolling linux/jammy R-4.5 pprof_1.0.3.tar.gz 1.2 MiB
1.0.3 rolling linux/noble R-4.5 pprof_1.0.3.tar.gz 1.2 MiB
1.0.3 rolling source/ R- pprof_1.0.3.tar.gz 846.0 KiB
1.0.3 latest linux/jammy R-4.5 pprof_1.0.3.tar.gz 1.2 MiB
1.0.3 latest linux/noble R-4.5 pprof_1.0.3.tar.gz 1.2 MiB
1.0.3 latest source/ R- pprof_1.0.3.tar.gz 846.0 KiB
1.0.3 2026-04-26 source/ R- pprof_1.0.3.tar.gz 846.0 KiB
1.0.3 2026-04-23 source/ R- pprof_1.0.3.tar.gz 846.0 KiB
1.0.3 2026-04-09 windows/windows R-4.5 pprof_1.0.3.zip 1.6 MiB
1.0.1 2025-04-20 source/ R- pprof_1.0.1.tar.gz 816.8 KiB

Dependencies (latest)

Imports

LinkingTo

Suggests