extractManipData function

Remove certain variables from the data set inside a sdc object.

Extract the manipulated data from an object of class sdcMicroObj-class

extractManipData(
  obj,
  ignoreKeyVars = FALSE,
  ignorePramVars = FALSE,
  ignoreNumVars = FALSE,
  ignoreGhostVars = FALSE,
  ignoreStrataVar = FALSE,
  randomizeRecords = "no"
)

Arguments

• obj: object of class sdcMicroObj-class

• ignoreKeyVars: If manipulated KeyVariables should be returned or the unchanged original variables

• ignorePramVars: if manipulated PramVariables should be returned or the unchanged original variables

• ignoreNumVars: if manipulated NumericVariables should be returned or the unchanged original variables

• ignoreGhostVars: if manipulated Ghost (linked) Variables should be returned or the unchanged original variables

• ignoreStrataVar: if manipulated StrataVariables should be returned or the unchanged original variables

• randomizeRecords: (logical) specifies, if the output records should be randomized. The following options are possible:

  • 'no': default, no randomization takes place
  • 'simple': records are just randomly swapped.
  • 'byHH': if slot 'hhId' is not NULL, the clusters defined by this variable are randomized across the dataset. If slot 'hhId' is NULL, the records or the dataset are randomly changed.
  • 'withinHH': if slot 'hhId' is not NULL, the clusters defined by this variable are randomized across the dataset and additionally, the order of records within the clusters are also randomly changed. If slot 'hhId' is NULL, the records or the dataset are randomly changed.

Returns

a data.frame containing the anonymized data set

Examples

## for objects of class sdcMicro:
data(testdata2)
sdc <- createSdcObj(testdata,
  keyVars=c('urbrur','roof'),
  numVars=c('expend','income','savings'), w='sampling_weight')
sdc <- removeDirectID(sdc, var="age")
dataM <- extractManipData(sdc)

Author(s)

Alexander Kowarik, Bernhard Meindl