Devore: Devore model

In RRTCS: Randomized Response Techniques for Complex Surveys

Description

Computes the randomized response estimation, its variance estimation and its confidence interval through the Devore model. The function can also return the transformed variable. The Devore model was proposed by Devore in 1977.

Usage

Devore(z,p,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 cards bearing the mark A
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

In the Devore model, the randomized response device presents to the sampled person labelled i a box containing a large number of identical cards with a proportion p,(0<p<1) bearing the mark A and the rest marked B (an innocuous attribute). The response solicited denoted by z_i takes the value y_i if i bears A and the card drawn is marked A. Otherwise z_i takes the value 1.

The transformed variable is r_i=\frac{z_i-(1-p)}{p} and the estimated variance is \widehat{V}_R(r_i)=r_i(r_i-1).

Value

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

References

Devore, J.L. (1977). A note on the randomized response technique. Communications in Statistics Theory and Methods 6: 1525-1529.

See Also

DevoreData

ResamplingVariance

Examples

data(DevoreData)
dat=with(DevoreData,data.frame(z,Pi))
p=0.7
cl=0.95
Devore(dat$z,p,dat$Pi,"total",cl)

RRTCS documentation built on April 21, 2021, 9:06 a.m.