The “amelia” Function in R

• Package: Amelia

• Purpose: Impute missing data using multiple imputation.

• General class: Imputation

• Required argument(s):

• x: A data frame with missing values.

• Notable optional arguments:

• m: Number of multiple imputations to generate (default is 5).

• idvars: Variables to be used as ID variables.

• ts: Time-series variable.

• polytime: Degree of the polynomial for time trends.

• emburn: Number of EM and burn-in iterations.

• bounds: Bounds for imputed values.

• boot.type: Type of bootstrap used.

• Example:

• # Load the required library
  library(Amelia)
  
  # Create a sample dataset with missing values
  data <- data.frame(
  id = 1:10,
  time = 1:10,
  x1 = c(1, 2, NA, 4, 5, 6, NA, 8, 9, 10),
  x2 = c(5, NA, 7, 8, 9, 10, 11, 12, NA, 15)
  )
  
  # Perform multiple imputation using the amelia function
  amelia_output <- amelia(x = data, m = 5, idvars = "id", ts = "time")
  
  # View the imputed datasets
  summary(amelia_output)

• In this example, the amelia function from the Amelia package is used to perform multiple imputation on a sample dataset with missing values. The dataset data contains missing values in columns x1 and x2. The amelia function generates 5 imputed datasets (m = 5) and specifies id as the ID variable and time as the time-series variable. The summary function is then used to view the imputed datasets.