RRTCS (version 0.0.4)

SoberanisCruz: SoberanisCruz model

Description

Computes the randomized response estimation, its variance estimation and its confidence interval through the SoberanisCruz model. The function can also return the transformed variable. The SoberanisCruz model was proposed by Soberanis Cruz et al. in 2008.

Usage

SoberanisCruz(z,p,alpha,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)

p

proportion of marked cards with the sensitive question

alpha

proportion of people with the innocuous attribute

pi

vector of the first-order inclusion probabilites

type

the estimator type: total or mean

cl

confidence leve

N

size of the population. By default it is NULL

pij

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

Value

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

Details

The SoberanisCruz model considers the introduction of an innocuous variable correlated with the sensitive variable. This variable does not affect individual sensitivity, and maintains reliability. The sampling procedure is the same as in the Horvitz model.

References

Soberanis Cruz, V., Ram<U+00ED>rez Valverde, G., P<U+00E9>rez Elizalde, S., Gonz<U+00E1>lez Cossio, F. (2008). Muestreo de respuestas aleatorizadas en poblaciones finitas: Un enfoque unificador. Agrociencia Vol. 42 N<U+00FA>m. 5 537-549.

See Also

SoberanisCruzData

Horvitz

ResamplingVariance

Examples

# NOT RUN {
data(SoberanisCruzData)
dat=with(SoberanisCruzData,data.frame(z,Pi))
p=0.7
alpha=0.5
cl=0.90
SoberanisCruz(dat$z,p,alpha,dat$Pi,"total",cl)
# }