R: Impute data sets in a purse

Impute.purse

R Documentation

Impute data sets in a purse

Description

This function imputes the target data set dset in each coin using the imputation function f_i. This is performed in the same way as the coin method Impute.coin(), but with one "special case" for panel data. If f_i = "impute_panel, the data sets inside the purse are imputed using the last available data point, using the impute_panel() function. In this case, coins are not imputed individually, but treated as a single data set. In this case, optionally set f_i_para = list(max_time = .) where . should be substituted with the maximum number of time points to search backwards for a non-NA value. See impute_panel() for more details. No further arguments need to be passed to impute_panel(). See vignette("imputation") for more details. See also Impute.coin() documentation.

Usage

## S3 method for class 'purse'
Impute(
  x,
  dset,
  f_i = NULL,
  f_i_para = NULL,
  impute_by = "column",
  group_level = NULL,
  use_group = NULL,
  normalise_first = NULL,
  write_to = NULL,
  ...
)

Arguments

`x`	A purse object
`dset`	The name of the data set to apply the function to, which should be accessible in `.$Data`.
`f_i`	An imputation function. For the "purse" class, if `f_i = "impute_panel` this is a special case: see details.
`f_i_para`	Further arguments to pass to `f_i`, other than `x`. See details.
`impute_by`	Specifies how to impute: if `"column"`, passes each column (indicator) separately as a numerical vector to `f_i`; if `"row"`, passes each row separately; and if `"df"` passes the entire data set (data frame) to `f_i`. The function called by `f_i` should be compatible with the type of data passed to it.
`group_level`	A level of the framework to use for grouping indicators. This is only relevant if `impute_by = "row"`. In that case, indicators will be split into their groups at the level specified by `group_level`, and imputation will be performed across rows of the group, rather than the whole data set. This can make more sense because indicators within a group are likely to be more similar.
`use_group`	Optional grouping variable name to pass to imputation function if this supports group imputation.
`normalise_first`	Logical: if `TRUE`, each column is normalised using a min-max operation before imputation. By default this is `FALSE` unless `impute_by = "row"`. See details.
`write_to`	Optional character string for naming the resulting data set in each coin. Data will be written to `.$Data[[write_to]]`. Default is `write_to == "Imputed"`.
`...`	arguments passed to or from other methods.

Value

An updated purse with imputed data sets added to each coin.

Examples

# see vignette("imputation")