RRTCS package. Application of Horvitz model to a real survey"

Horvitz model

In the Horvitz 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 whose population proportion $\alpha$ is known).
The response solicited denoted by $z_i$ takes the value $y_i$ if $i$ bears $A$ and the card drawn is marked $A$ or if $i$ bears $B$ and the card drawn is marked $B$. Otherwise $z_i$ takes the value 0. Sin titulo

Horvitz model example

The file data "HorvitzDataRealSurvey.rda" stores a sample, extracted by simple random sampling without replacement, of size 710. With these data we estimate the prevalence of students who have sensitive characteristics set out below.
The randomized response technique used is Horvitz model (Horvitz et al, 1967 and Greenberg et al., 1969) with parameter $p=0.5$

Horvitz model survey design

In this model an additional questionnaire with the following characteristics is required:

The survey is

Sin titulo

To estimate results, you must have the response probabilities of non-sensitive questions:

Sin titulo

Horvitz model technique description

In order to give more confidence to the respondent, he was given a booklet of instructions:

This procedure must be repeated for each question.

The respondent only had to put on the question sheet a cross in the chosen answers, and then he deposited the survey sheet in an urn.

We store the answers to senstive questions in data.frame (HorvitzDataRealSurvey.rda).

Horvitz function

We use the Horvitz function to obtain the estimates:

library("RRTCS")
N=10777
n=710
data(HorvitzDataRealSurvey)
p=0.5
alpha=c(1/12,1/10,20/30,1/10,10/30,1/12)
pi=rep(n/N,n)
cl=0.95
out1=Horvitz(HorvitzDataRealSurvey$copied,p,alpha[1],pi,"mean",cl,N)
out1
out2=Horvitz(HorvitzDataRealSurvey$fought,p,alpha[2],pi,"mean",cl,N)
out2
out3=Horvitz(HorvitzDataRealSurvey$bullied,p,alpha[3],pi,"mean",cl,N)
out3
out4=Horvitz(HorvitzDataRealSurvey$bullying,p,alpha[4],pi,"mean",cl,N)
out4
out5=Horvitz(HorvitzDataRealSurvey$drug,p,alpha[5],pi,"mean",cl,N)
out5
out6=Horvitz(HorvitzDataRealSurvey$sex,p,alpha[6],pi,"mean",cl,N)
out6

References

Greenberg, B.G., Abul-Ela, A.L., Simmons, W.R., Horvitz, D.G. (1969). The unrelated question RR model: Theoretical framework. Journal of the American Statistical Association, 64, 520-539.

Horvitz, D.G., Shah, B.V., Simmons, W.R. (1967). The unrelated question RR model. Proceedings of the Social Statistics Section of the American Statistical Association. 65-72. Alexandria, VA: ASA.



Try the RRTCS package in your browser

Any scripts or data that you put into this service are public.

RRTCS documentation built on May 29, 2017, 9:43 a.m.