Perform Structural Missing Data Investigations
Objects exported from other packages
Computes mean/median absolute standardized mean differences between ob...
This is a utility function to help check input data and covariates pro...
Computes three group missing data summary diagnostics
Computes hotelling's multivariate t-test
Computes Little's test
Create binary missing indicator variables by two different strategies
Computes association between missingness and outcome
Computes random forest-based AUC
Takes an object of class smdi and styles it to a publication-ready gt ...
Utility helper to give a light summary of partially observed covariate...
Quick ggplot2 barchart visualization of partially observed/missing var...
smdi: Perform Structural Missing Data Investigations
An easy to use implementation of routine structural missing data diagnostics with functions to visualize the proportions of missing observations, investigate missing data patterns and conduct various empirical missing data diagnostic tests. Reference: Weberpals J, Raman SR, Shaw PA, Lee H, Hammill BG, Toh S, Connolly JG, Dandreo KJ, Tian F, Liu W, Li J, Hernández-Muñoz JJ, Glynn RJ, Desai RJ. smdi: an R package to perform structural missing data investigations on partially observed confounders in real-world evidence studies. JAMIA Open. 2024 Jan 31;7(1):ooae008. <doi:10.1093/jamiaopen/ooae008>.
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