smdi_check_covar

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

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>.

Janick Weberpals

smdi

Perform Structural Missing Data Investigations

smdi_check_covar function

<dl><dt>data</dt>
<dd>dataframe or tibble object with partially observed/missing variables</dd>
<dt>covar</dt>
<dd>character covariate or covariate vector with partially observed variable/column name(s) to investigate. If NULL, the function automatically looks for and includes all columns with at least one missing observation</dd></dl>

Arguments

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

<dl>

<dt>data</dt>
<dd>dataframe or tibble object with partially observed/missing variables</dd>


<dt>covar</dt>
<dd>character covariate or covariate vector with partially observed variable/column name(s) to investigate. If NULL, the function automatically looks for and includes all columns with at least one missing observation</dd>

</dl>

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

Description

Usage

Value

Arguments