This package is considered a duplicate. The official version of this package is found at:https://um-kevinhe.r-universe.dev/pprof

Package: pprof 1.0.1

Xiaohan Liu

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>.

Authors:Xiaohan Liu [aut, cre], Lingfeng Luo [aut], Yubo Shao [aut], Xiangeng Fang [aut], Wenbo Wu [aut], Kevin He [aut]

pprof_1.0.1.tar.gz
pprof_1.0.1.tar.gz(r-4.5-noble)pprof_1.0.1.tar.gz(r-4.4-noble)
pprof_1.0.1.tgz(r-4.4-emscripten)pprof_1.0.1.tgz(r-4.3-emscripten)
pprof.pdf |pprof.html✨
pprof/json (API)

# Install 'pprof' in R:

install.packages('pprof', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/um-kevinhe/pprof/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

ExampleDataBinary - Example data with binary outcomes
ExampleDataLinear - Example data with continuous outcomes
ecls_data - Early Childhood Longitudinal Study Dataset

openblas cpp openmp

1.70 score 3 scripts 8 exports 124 dependencies

Last updated 18 days agofrom:5a867754e2. Checks:OK: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Dec 13 2024
R-4.5-linux-x86_64	OK	Dec 13 2024

Exports:bar_plot caterpillar_plot data_check linear_fe linear_re logis_fe SM_output test

Dependencies:abind backports base64enc boot broom bslib cachem car carData caret class cli clock codetools colorspace commonmark cowplot cpp11 crayon data.table Deriv diagram digest doBy dplyr e1071 fansi farver fastmap fontawesome foreach Formula fs future future.apply generics ggplot2 globals glue goftest gower gridExtra gtable hardhat htmltools httpuv ipred isoband iterators jquerylib jsonlite KernSmooth labeling later lattice lava lifecycle listenv lme4 lubridate magrittr MASS Matrix MatrixModels memoise mgcv microbenchmark mime minqa ModelMetrics modelr munsell nlme nloptr nnet nortest numDeriv olsrr parallelly pbkrtest pillar pkgconfig plyr poibin pROC prodlim progressr promises proxy purrr quantreg R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen RcppParallel recipes reshape2 rlang rpart sass scales shape shiny sourcetools SparseM SQUAREM stringi stringr survival tibble tidyr tidyselect timechange timeDate tzdb utf8 vctrs viridisLite withr xplorerr xtable

Help page	Topics
Get a bar plot for flagging percentage overall and stratified by provider sizes	bar_plot
Get a caterpillar plot to display confidence intervals for standardized measures	caterpillar_plot
Get confidence intervals for provider effects or standardized measures from a fitted 'linear_fe' object	confint.linear_fe
Get confidence intervals for provider effects or standardized measures from a fitted 'linear_re' object	confint.linear_re
Get confidence intervals for provider effects or standardized measures from a fitted 'logis_fe' object	confint.logis_fe
Data quality check function	data_check
Early Childhood Longitudinal Study Dataset	ecls_data
Example data with binary outcomes	ExampleDataBinary
Example data with continuous outcomes	ExampleDataLinear
Main function for fitting the fixed effect linear model	linear_fe
Main Function for fitting the random effect linear model	linear_re
Main function for fitting the fixed effect logistic model	logis_fe
Get funnel plot from a fitted 'linear_fe' object for institutional comparisons	plot.linear_fe
Get funnel plot from a fitted 'logis_fe' object for institutional comparisons	plot.logis_fe
Generic function for calculating standardized measures	SM_output
Calculate direct/indirect standardized differences from a fitted 'linear_fe' object	SM_output.linear_fe
Calculate direct/indirect standardized differences from a fitted 'linear_re' object	SM_output.linear_re
Calculate direct/indirect standardized ratios/rates from a fitted 'logis_fe' object	SM_output.logis_fe
Result Summaries of Covariate Estimates from a fitted 'linear_fe' or 'linear_re' object	summary.linear_fe summary.linear_re
Result Summaries of Covariate Estimates from a fitted 'logis_fe' object	summary.logis_fe
Generic function for hypothesis testing of provider effects	test
Conduct hypothesis testing for provider effects from a fitted 'linear_fe' object	test.linear_fe
Conduct hypothesis testing for provider effects from a fitted 'linear_re' object	test.linear_re
Conduct hypothesis testing for provider effects from a fitted 'logis_fe' object	test.logis_fe

Package: pprof 1.0.1

pprof: Modeling, Standardization and Testing for Provider Profiling

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)