pram_strata: Post Randomization

Description

To be used on categorical data. It randomly change the values of variables on selected records (usually the risky ones) according to an invariant probability transition matrix.

Usage

pram_strata(obj,variables,...)#,  strata_variables = NULL, weights = NULL,
  #seed = NULL, missing = -999, pd = 0.8,alpha = 0.5)
## S3 method for class 'pram_strata':
print(x, ...)

Arguments

obj

Input data or object of class sdcMicroObj

variables

Names of variables for Post Randomization

...

see arguments below

strata_variables

Names of variables for stratification

weights

a weight for each variable

seed

Integer value for the random seed

missing

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

Output of pram_strata

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 new variables with the suffix "_pram" will be created.

References

http://www.gnu.org/software/glpk http://www.ccsr.ac.uk/sars/guide/2001/pram.pdf

Examples

Run this code

data(testdata)
  res <- pram_strata(testdata,variables="roof",strata_variables=c("urbrur","sex"))
  print.pram_strata(res)
  res1 <- pram_strata(testdata,variables=c("roof","walls","water"),strata_variables=c("urbrur","sex"))
  print.pram_strata(res1)
  res2 <- pram_strata(testdata,variables=c("roof","walls","water"),strata_variables=NULL)
  print.pram_strata(res2)
  
  ## 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_strata(sdc, variables=c("urbrur"))