Impute the mode value into a vector with missing values

Impute the mode value into a vector with missing values

Usage

impute_mode(x)

# S3 method for default
impute_mode(x)

# S3 method for integer
impute_mode(x)

# S3 method for factor
impute_mode(x)

Arguments

x

vector

This approach adapts examples provided from stack overflow, and for the integer case, just rounds the value. While this can be useful if you are imputing specific values, however we would generally recommend to impute using other model based approaches. See the simputation package, for example simputation::impute_lm().

Value

vector with mode values replaced

Examples

vec <- rnorm(10)

vec[sample(1:10, 3)] <- NA

impute_mode(vec)
#>  [1]  1.371914294  0.413380638 -1.669939609  0.069016915  0.069016915
#>  [6] -1.158660464  0.001326548 -1.771324596  0.018509032  0.069016915

library(dplyr)

dat <- tibble(
  num = rnorm(10),
  int = rpois(10, 5),
  fct = factor(LETTERS[1:10])
) %>%
  mutate(
    across(
      everything(),
      \(x) set_prop_miss(x, prop = 0.25)
    )
  )

dat
#> # A tibble: 10 × 3
#>        num   int fct  
#>      <dbl> <int> <fct>
#>  1 -0.100      6 A    
#>  2 -0.342      4 B    
#>  3 -0.108     NA C    
#>  4  1.51       6 D    
#>  5  0.202     10 NA   
#>  6  2.26       3 F    
#>  7 NA         NA NA   
#>  8 -1.30       8 H    
#>  9 NA          6 I    
#> 10 -0.0709     3 J    


dat %>%
  nabular() %>%
  mutate(
    num = impute_mode(num),
    int = impute_mode(int),
    fct = impute_mode(fct)
  )
#> # A tibble: 10 × 6
#>        num   int fct   num_NA int_NA fct_NA
#>      <dbl> <dbl> <fct> <fct>  <fct>  <fct> 
#>  1 -0.100      6 A     !NA    !NA    !NA   
#>  2 -0.342      4 B     !NA    !NA    !NA   
#>  3 -0.108      6 C     !NA    NA     !NA   
#>  4  1.51       6 D     !NA    !NA    !NA   
#>  5  0.202     10 B     !NA    !NA    NA    
#>  6  2.26       3 F     !NA    !NA    !NA   
#>  7 -0.0964     6 B     NA     NA     NA    
#>  8 -1.30       8 H     !NA    !NA    !NA   
#>  9 -0.0964     6 I     NA     !NA    !NA   
#> 10 -0.0709     3 J     !NA    !NA    !NA