sdcMicro (version 3.1.1)

measure_risk: Measure Risk for weighted or unweighted data / Individual risk to household risk / Compute a risk threshold based on a global risk value

Description

measure risk like in mu-argus / To be used when risk of disclosure for individuals within a family is considered to be statistical independent. This is the assumption made in mu-Argus risk model. / To be used when the risk measurement at individual level can be used to calculate the file level risk by taking the average of the individual risk.

Usage

measure_risk(data,variables,weight_variable=NULL,missing=-999,l_recurs_c=2,ldiv_index=NULL)
## S3 method for class 'measure_risk':
print(x, ...)
measure_hier(data,variables,weight_variable=NULL,hid,missing=-999)
## S3 method for class 'measure_hier':
print(x, ...)
measure_thres(data,variables,weight_variable=NULL,missing=-999)
## S3 method for class 'measure_thres':
print(x, ...)

Arguments

data

Input data

variables

Names of key variables

weight_variable

name of variable containing sample weights

hid

Household ID

missing

A integer value to be used as missing value in the C++ routine

l_recurs_c

L-Diversity Constant

ldiv_index

indices of the variables used for l-diversity

x

Output of measure_risk, measure_hier or measure_thres

...

currently unused

Value

• xx

References

http://neon.vb.cbs.nl/casc/Software/MuManual4.1.pdf

See Also

measure_hier

Examples

# measure_risk
  data(testdata)
  res <- measure_risk(testdata,c("urbrur","roof","walls","water","sex"))
  print(res)
  head(res$Res)
  resw <- measure_risk(testdata,c("urbrur","roof","walls","water","sex"),weight_variable="sampling_weight")
  print(resw)
  head(resw$Res)
  res1 <- measure_risk(testdata,c("urbrur","roof","walls","water","sex"),ldiv_index=c(1))
  print(res1)
  head(res1$Mat_Risk)
  res2 <- measure_risk(testdata,c("urbrur","roof","walls","water","sex"),ldiv_index=c(1,2))
  print(res2)
  head(res2$Mat_Risk)
  # measure_hier
  resh <- measure_hier(testdata,c("urbrur","roof","walls","water","sex"),weight_variable="sampling_weight",hid="ori_hid")
  print(resh)
  # measure_thres
  rest <- measure_thres(testdata,c("urbrur","roof","walls","water","sex"),weight_variable="sampling_weight")
  print(rest)