R: Prioritize Variables with Joint Variable Importance Plot in Observational Study Design

# Prioritize Variables with Joint Variable Importance Plot in Observational Study Design

## Documentation for package ‘jointVIP’ version 1.0.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

add_bias_curves | support function to plot bias curves
add_variable_labels | support function to plot variable text labels
bootstrap.plot | plot the bootstrap version of the jointVIP object
brfss | 2015 Behavioral Risk Factor Surveillance System
ceiling_dec | support function for ceiling function with decimals
check_measures | Check measures Check to see if there is any missing values or variables without any variation or identical rows (only unique rows will be used)
create_jointVIP | create jointVIP object
create_post_jointVIP | create post_jointVIP object
floor_dec | support function for floor function with decimals
get_boot_measures | Calculate bootstrapped variation additional tool to help calculate the uncertainty of each variable's bias
get_measures | Prepare data frame to plot standardized omitted variable bias Marginal standardized mean differences and outcome correlation
get_post_measures | Post-measures data frame to plot post-standardized omitted variable bias
one_hot | support function for one-hot encoding
plot.jointVIP | plot the jointVIP object
plot.post_jointVIP | plot the post_jointVIP object this plot uses the same custom options as the jointVIP object
print.jointVIP | Obtains a print for jointVIP object
print.post_jointVIP | Obtains a print for post_jointVIP object
summary.jointVIP | Obtains a summary jointVIP object
summary.post_jointVIP | Obtains a summary post_jointVIP object