scholarly journals Estimation of the proportion of a sensitive attribute based on a two-stage randomized response model with stratified unequal probability sampling

2014 ◽  
Vol 28 (3) ◽  
pp. 381-408 ◽  
Author(s):  
Gi-Sung Lee ◽  
Ki-Hak Hong ◽  
Jong-Min Kim ◽  
Chang-Kyoon Son
Keyword(s):  
Response Model ◽  
Randomized Response ◽  
Two Stage ◽  
Probability Sampling ◽  
Unequal Probability Sampling ◽  
Unequal Probability ◽  
Sensitive Attribute ◽  
Randomized Response Model

An Improved Two-stage Randomized Response Model for Estimating the Proportion of Sensitive Attribute

2021 ◽  
pp. 004912412110099
Author(s):  
Ghulam Narjis ◽  
Javid Shabbir
Keyword(s):  
Random Sampling ◽  
Stratified Random Sampling ◽  
Response Model ◽  
Randomized Response Technique ◽  
Randomized Response ◽  
Two Stage ◽  
Sensitive Attribute ◽  
Mean And Variance ◽  
Efficiency Comparison ◽  
Randomized Response Model

The randomized response technique (RRT) is an effective method designed to obtain the stigmatized information from respondents while assuring the privacy. In this study, we propose a new two-stage RRT model to estimate the prevalence of sensitive attribute ([Formula: see text]). A simulation study shows that the empirical mean and variance of proposed estimator are close to corresponding theoretical values. The utility of proposed two-stage RRT model under stratification is also explored. An efficiency comparison between proposed two-stage RRT model and some existing RRT models is carried out numerically under simple and stratified random sampling.

Evaluation of sampling alternatives to quantify tree leaf area

2003 ◽  
Vol 33 (1) ◽  
pp. 82-95 ◽  
Author(s):  
H Temesgen
Keyword(s):  
Leaf Area ◽  
Poor Performance ◽  
Tree Crown ◽  
Two Stage ◽  
Zero Bias ◽  
Probability Sampling ◽  
First Order ◽  
Unequal Probability Sampling ◽  
Unequal Probability ◽  
Tree Leaf

High within- and among-tree crown variation have contributed to the difficulty of tree-crown sampling and single-tree leaf area (area available for photosynthesis) estimation. Using reconstructed trees, simulations were used to compare five sampling designs for bias, mean square error (MSE), and distribution of the estimates. All sampling designs showed nearly zero bias. For most sample trees, stratified random sampling resulted in the lowest MSE values, followed by ellipsoidal, two-stage systematic, simple random, and then by two-stage unequal probability sampling. The poor performance of two-stage unequal probability sampling can be ascribed to the unequal probability of inclusion of first-order branches and twigs.

Sign in / Sign up

Export Citation Format

Share Document