sdcMicro (version 5.7.8)

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

Description

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

Usage

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

Value

a data.frame containing the anonymized data set

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.

Author

Alexander Kowarik, Bernhard Meindl

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)