ChaudhuriChristofides {RRTCS}

Chaudhuri-Christofides model

Description

Computes the randomized response estimation, its variance estimation and its confidence interval through the Chaudhuri-Christofides model. The function can also return the transformed variable. The Chaudhuri-Christofides model can be seen in Chaudhuri and Christofides (2013, page 97).

Usage

ChaudhuriChristofides(z,mu,sigma,pi,type=c("total","mean"),cl,N=NULL,pij=NULL)

Arguments

z

vector of the observed variable; its length is equal to n (the sample size)

mu

vector with the means of the scramble variables

sigma

vector with the standard deviations of the scramble variables

pi

vector of the first-order inclusion probabilities

type

the estimator type: total or mean

cl

confidence level

N

size of the population. By default it is NULL

pij

matrix of the second-order inclusion probabilities. By default it is NULL

Details

The randomized response given by the person i is z_i=y_iS_1+S_2 where S_1,S_2 are scramble variables, whose mean \mu and standard deviation \sigma are known.

Value

Point and confidence estimates of the sensitive characteristics using the Chaudhuri-Christofides model. The transformed variable is also reported, if required.

References

Chaudhuri, A., and Christofides, T.C. (2013) Indirect Questioning in Sample Surveys. Springer-Verlag Berlin Heidelberg.

See Also

ChaudhuriChristofidesData

ChaudhuriChristofidesDatapij

ResamplingVariance

Examples

N=417
data(ChaudhuriChristofidesData)
dat=with(ChaudhuriChristofidesData,data.frame(z,Pi))
mu=c(6,6)
sigma=sqrt(c(10,10))
cl=0.95
data(ChaudhuriChristofidesDatapij)
ChaudhuriChristofides(dat$z,mu,sigma,dat$Pi,"mean",cl,pij=ChaudhuriChristofidesDatapij)