primarySuppression: Apply primary suppression

In bernhard-da/sdcTable: Methods for Statistical Disclosure Control in Tabular Data

Description

Function primarySuppression() is used to identify and suppress primary sensitive table cells in sdcProblem objects. Argument type allows to select a rule that should be used to identify primary sensitive cells. At the moment it is possible to identify and suppress sensitive table cells using the frequency-rule, the nk-dominance rule and the p-percent rule.

Usage

primarySuppression(object, type, ...)

Arguments

object	a sdcProblem object
type	character vector of length 1 defining the primary suppression rule. Allowed types are: freq: apply frequency rule with parameters maxN and allowZeros nk: apply nk-dominance rule with parameters n, k and numVarInd p: apply p-percent rule with parameters p and numVarInd pq: apply pq-rule with parameters p and q
...	parameters used in the identification of primary sensitive cells. Parameters that can be modified|changed are: maxN: numeric vector of length 1 used when applying the frequency rule. All cells having counts <= maxN are set as primary suppressed. The default value of maxN is 3. allowZeros: logical vector of length 1 specifying if empty cells (count==0) should be considered sensitive when using the frequency rule. The default value of allowZeros is FALSE so that empty cells are not considered primary sensitive by default. p: numeric vector of length 1 specifying parameter p that is used when applying the p-percent rule with default value of 80. pq: numeric vector of length 2 specifying parameters p and q that are used when applying the pq-rule with the default being c(25, 50). n: numeric vector of length 1 specifying parameter n that is used when applying the nk-dominance rule. Parameter n is set to 2 by default. k: scalar numeric specifying parameter k that is used when applying the nk-dominance rule. Parameter n is set to 85 by default. numVarName: character scalar specifying the name of the numerical variable that should be used to identify cells that are dominated by dominance rules (p-rule, pq-rule or nk-rule). If type is either 'nk', 'p' or 'pq', it is mandatory to specify either numVarInd or numVarName. numVarInd: same as numVarName but a scalar numeric specifying the index of the variable is expected. If both numVarName and numVarInd are specified, numVarName is used.

Value

a sdcProblem object

Note

the nk-dominance rule, the p-percent rule and the pq-rule can only be applied if micro data have been used as input data to function makeProblem()

Author(s)

Bernhard Meindl [e-mail]

Examples

# load micro data
data("microData1", package = "sdcTable")

# load problem (as it was created in the example in ?makeProblem
data("problem", package = "sdcTable")

# we have a look at the frequency table by gender and region
xtabs(rep(1, nrow(microData1)) ~ gender + region, data = microData1)

# 2 units contribute to cell with region=='A' and gender=='female'
# --> this cell is considered sensitive according the the
# freq-rule with 'maxN' equal to 2!
p1 <- primarySuppression(
  object = problem,
  type = "freq",
  maxN = 2
)

# we can also apply a p-percent rule with parameter "p" being 30 as below.
# This is only possible if we are dealing with micro data and we also
# have to specify the name of a numeric variable.
p2 <- primarySuppression(
  object = problem,
  type = "p",
  p = 30,
  numVarName = "val"
)

# looking at anonymization states we see, that one cell is primary
# suppressed (sdcStatus == "u")
# the remaining cells are possible candidates for secondary cell
# suppression (sdcStatus == "s") given the frequency rule with
# parameter "maxN = 2".
#
# Applying the p-percent rule with parameter 'p = 30' resulted in
# two primary suppressions.
data.frame(
  p1_sdc = getInfo(p1, type = "sdcStatus"),
  p2_sdc = getInfo(p2, type = "sdcStatus")
)

bernhard-da/sdcTable documentation built on June 10, 2019, 4:54 a.m.