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smdi (version 0.3.1)

Perform Structural Missing Data Investigations

Description

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. .

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Version

Install

install.packages('smdi')

Monthly Downloads

248

Version

0.3.1

License

GPL (>= 3)

Maintainer

Janick Weberpals

Last Published

October 4th, 2024

Functions in smdi (0.3.1)

smdi_data_complete

smdi exemplary lung cancer dataset (with complete data)
smdi_diagnose

Computes three group missing data summary diagnostics
smdi_check_covar

This is a utility function to help check input data and covariates provided
smdi_little

Computes Little's test
smdi_hotelling

Computes hotelling's multivariate t-test
smdi_asmd

Computes mean/median absolute standardized mean differences between observed and missing observations
smdi_na_indicator

Create binary missing indicator variables by two different strategies
smdi_style_gt

Takes an object of class smdi and styles it to a publication-ready gt table
smdi_vis

Quick ggplot2 barchart visualization of partially observed/missing variables
smdi_summarize

Utility helper to give a light summary of partially observed covariates
smdi_data

smdi exemplary lung cancer dataset
smdi-package

smdi: Perform Structural Missing Data Investigations
reexports

Objects exported from other packages
smdi_outcome

Computes association between missingness and outcome
smdi_rf

Computes random forest-based AUC