Return a tibble in shadow matrix form, where the variables are the same but have a suffix _NA attached to distinguish them.

as_shadow(data, ...)

Arguments

data

dataframe

...

selected variables to use

Value

appended shadow with column names

Details

Representing missing data structure is achieved using the shadow matrix, introduced in Swayne and Buja. The shadow matrix is the same dimension as the data, and consists of binary indicators of missingness of data values, where missing is represented as "NA", and not missing is represented as "!NA". Although these may be represented as 1 and 0, respectively.

Examples

as_shadow(airquality)
#> # A tibble: 153 x 6 #> Ozone_NA Solar.R_NA Wind_NA Temp_NA Month_NA Day_NA #> <fct> <fct> <fct> <fct> <fct> <fct> #> 1 !NA !NA !NA !NA !NA !NA #> 2 !NA !NA !NA !NA !NA !NA #> 3 !NA !NA !NA !NA !NA !NA #> 4 !NA !NA !NA !NA !NA !NA #> 5 NA NA !NA !NA !NA !NA #> 6 !NA NA !NA !NA !NA !NA #> 7 !NA !NA !NA !NA !NA !NA #> 8 !NA !NA !NA !NA !NA !NA #> 9 !NA !NA !NA !NA !NA !NA #> 10 NA !NA !NA !NA !NA !NA #> # … with 143 more rows