impute_panel {COINr}

R Documentation

Impute panel data

Description

Given a data frame of panel data, with a time-index column time_col and a unit ID column unit_col, imputes other columns using the entry from the latest available time point.

Usage

impute_panel(
  iData,
  time_col = NULL,
  unit_col = NULL,
  cols = NULL,
  max_time = NULL
)

Arguments

iData	A data frame of indicator data, containing a time index column time_col, a unit code column unit_col, and other numerical columns to be imputed.
time_col	The name of a column found in iData to be used as the time index column. Must point to a numeric column.
unit_col	The name of a column found in iData to be used as the unit code/ID column. Must point to a character column.
cols	Optionally, a character vector of names of columns to impute. If NULL (default), all columns apart from time_col and unit_col will be imputed where possible.
max_time	The maximum number of time points to look backwards to impute from. E.g. if max_time = 1, if an NA is found at time t, it will only look for a replacement value at t-1 but not in any time points before that. By default, searches all time points available.

Details

This presumes that there are multiple observations for each unit code, i.e. one per time point. It then searches for any missing values in the target year, and replaces them with the equivalent points from previous time points. It will replace using the most recently available point.

Value

A list containing:

• .$iData_imp: An iData format data frame with missing data imputed using previous time points (where possible).

• .$DataT: A data frame in the same format as iData, where each entry shows which time point each data point came from.

Examples

# Copy example panel data
iData_p <- ASEM_iData_p

# we introduce two NAs: one for NZ in 2022 in LPI indicator
iData_p$LPI[iData_p$uCode == "NZ" & iData_p$Time == 2022] <-  NA
# one for AT, also in 2022, but for Flights indicator
iData_p$Flights[iData_p$uCode == "AT" & iData_p$Time == 2022] <- NA

# impute: target only the two columns where NAs introduced
l_imp <- impute_panel(iData_p, cols = c("LPI", "Flights"))
# get imputed df
iData_imp <- l_imp$iData_imp

# check the output is what we expect: both NAs introduced should now have 2021 values
iData_imp$LPI[iData_imp$uCode == "NZ" & iData_imp$Time == 2022] ==
  ASEM_iData_p$LPI[ASEM_iData_p$uCode == "NZ" & ASEM_iData_p$Time == 2021]

iData_imp$Flights[iData_imp$uCode == "AT" & iData_imp$Time == 2022] ==
  ASEM_iData_p$Flights[ASEM_iData_p$uCode == "AT" & ASEM_iData_p$Time == 2021]

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