missingness_indicators: Return matrix of missingness indicators for a dataframe or...
In ck37r: Chris Kennedy's R Toolkit

Description Usage Arguments Value See Also Examples

Return matrix of missingness indicators for a dataframe or matrix. Removes constant or collinear indicators.

1 2	missingness_indicators(data, prefix = "miss_", remove_constant = T, remove_collinear = T, skip_vars = c(), verbose = F)

`data`	Dataframe or matrix to analyze for missingness.
`prefix`	Name prefix for new indicator columns.
`remove_constant`	Remove any indicators that are all 0 or all 1.
`remove_collinear`	Remove any indicators that are collinear with each other.
`skip_vars`	Vector of variable names to skip.
`verbose`	If TRUE, print additional information.

Matrix of missingness indicators

impute_missing_values

# Load a test dataset.
data(PimaIndiansDiabetes2, package = "mlbench")

# Check for missing values.
colSums(is.na(PimaIndiansDiabetes2))

# Generate missingness indicators; skip outcome variable.
indicators = missingness_indicators(PimaIndiansDiabetes2, skip_vars = "diabetes")

# Check missingness.
colSums(indicators)