# Perform Structural Missing Data Investigations

## Documentation for package ‘smdi’ version 0.3.2

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

## Help Pages

smdi_asmd | Computes mean/median absolute standardized mean differences between observed and missing observations
smdi_check_covar | This is a utility function to help check input data and covariates provided
smdi_data | smdi exemplary lung cancer dataset
smdi_data_complete | smdi exemplary lung cancer dataset (with complete data)
smdi_diagnose | Computes three group missing data summary diagnostics
smdi_hotelling | Computes hotelling's multivariate t-test
smdi_little | Computes Little's test
smdi_na_indicator | Create binary missing indicator variables by two different strategies
smdi_outcome | Computes association between missingness and outcome
smdi_rf | Computes random forest-based AUC
smdi_style_gt | Takes an object of class smdi and styles it to a publication-ready gt table
smdi_summarize | Utility helper to give a light summary of partially observed covariates
smdi_vis | Quick ggplot2 barchart visualization of partially observed/missing variables