TY - JOUR
T1 - Bayes linear estimator for two-stage and stratified randomized response models
AU - Son, Chang Kyoon
AU - Kim, Jong-Min
PY - 2015/11/16
Y1 - 2015/11/16
N2 - In this paper, we suggest the Bayes linear estimator (BLE) for randomized response model (RRM) to improve the efficiency of RR estimators, only using the first and second prior moments. The randomized response model is an indirect questioning technique used to protect the privacy of respondents in a survey regarding a sensitive characteristic. Meanwhile Bayes linear estimation is useful for parameter estimation compared to the typical Bayesian method because it only uses the first and second prior knowledge of the variable of interest. Also, it has an advantage of robustness with the distribution. We suggest the Bayes linear estimators for the two-stage and the stratified RRM and find the optimal sample size to minimize the Bayes risk for the stratified RRM. Also, we show the difference in efficiency between the Bayes linear estimators and the typical non-Bayesian RR estimators by simulation study.
AB - In this paper, we suggest the Bayes linear estimator (BLE) for randomized response model (RRM) to improve the efficiency of RR estimators, only using the first and second prior moments. The randomized response model is an indirect questioning technique used to protect the privacy of respondents in a survey regarding a sensitive characteristic. Meanwhile Bayes linear estimation is useful for parameter estimation compared to the typical Bayesian method because it only uses the first and second prior knowledge of the variable of interest. Also, it has an advantage of robustness with the distribution. We suggest the Bayes linear estimators for the two-stage and the stratified RRM and find the optimal sample size to minimize the Bayes risk for the stratified RRM. Also, we show the difference in efficiency between the Bayes linear estimators and the typical non-Bayesian RR estimators by simulation study.
KW - Bayes linear estimator
KW - optimal sampling design
KW - stratified randomized response model
KW - two-stage randomized response model
UR - http://www.scopus.com/inward/record.url?scp=84947574607&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84947574607&partnerID=8YFLogxK
U2 - 10.3233/MAS-150336
DO - 10.3233/MAS-150336
M3 - Article
AN - SCOPUS:84947574607
SN - 1574-1699
VL - 10
SP - 321
EP - 333
JO - Model Assisted Statistics and Applications
JF - Model Assisted Statistics and Applications
IS - 4
ER -