# Modeling, Standardization and Testing for Provider Profiling

## Documentation for package ‘pprof’ version 1.0.3

- DESCRIPTION file
- Package README

## Help Pages

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