mad: Compute variable-wise mean absolute differences (MAD) between...

In pdwaggoner/hdImpute: A Batch Process for High Dimensional Imputation

Compute variable-wise mean absolute differences (MAD) between original and imputed dataframes.

Description

Compute variable-wise mean absolute differences (MAD) between original and imputed dataframes.

Usage

mad(original, imputed, round)

Arguments

original	A data frame or tibble with original values.
imputed	A data frame or tibble that has been imputed/completed.
round	Integer. Number of places to round MAD scores. Default set to 3.

Value

'mad_scores' as 'p' x 2 tibble. One row for each variable in original, from 1 to 'p'. Two columns: first is variable names ('var') and second is associated MAD score ('mad') as percentages for each variable.

Examples

## Not run: 
mad(original = original_data, imputed = imputed_data, round = 3)

## End(Not run)

pdwaggoner/hdImpute documentation built on Sept. 2, 2024, 6:41 a.m.