sdcMicro (version 4.0.2)

pram: Post RAndomisation Method (PRAM)

Description

PRAM is a probabilistic, perturbative method which can be applied on categorical variables.

Usage

pram(obj,keyVar=NULL,...)#x, pd=0.8, alpha=0.5)

Arguments

obj

a numeric vector or factor, data.frame or object of class sdcMicroObj

keyVar

name of the keyVar that should be prammed

...

see arguments below

pd

minimum diagonal entries for the generated transition matrix P. Either a vector of length 1 or a vector of length ( number of categories ).

alpha

amount of perturbation for the invariant Pram method

Value

• a modified sdcMicroObj object or the following list
• x
  original vector
• xpramed
  the perturbed vector
• pd
  randomly generated diagonal entry of the P (between original pd and 1)
• Rs
  invariant transition matrix
• alpha
  amount of perturbation for the invariant Pram method

Details

The method is implemented exactly as described in the citation in the references. First a transition matrix is created in that way, that the diagonal entries of a matrix P are random numbers between pd and 1. The remaining entries of the matrix are generated such that the rowSums of the matrix is 1. Then a invariant transition matrix is generated.

References

Shlomo, Natalie and de Waal, Ton (2006) Protection of Micro-data Subject to Edit Constraints Against Statistical Disclosure. Southampton, UK, Southampton Statistical Sciences Research Institute, 36pp. (S3RI Methodology Working Papers, M06/16)

Examples

set.seed(123)
x <- factor(sample(1:4, 250, replace=TRUE))
pr1 <- pram(x)
length(which(pr1$x == x))
x2 <- as.factor(sample(1:4, 250, replace=TRUE))
length(which(pram(x2)$x == x2))

data(free1)
free1 <- data.frame(free1)
free1[,"MARSTAT"] <- as.factor(free1[,"MARSTAT"])
marstatPramed <- pram(free1[,"MARSTAT"])  

  ## for objects of class sdcMicro:
  data(testdata2)
  sdc <- createSdcObj(testdata2, keyVars=c('urbrur','roof','walls','water','electcon','relat','sex'), 
           numVars=c('expend','income','savings'), w='sampling_weight')
  sdc <- pram(sdc,keyVar="water")