Item Count Technique in Ranked Set Sampling

In situations where the estimation of the proportion of sensitive variables relies on the observations of real measurements that are difficult to obtain, there is a need to combine indirect questioning techniques. In the present work, the authors will focus on the item count technique, with alternative methods of sampling, such as the ranked set sampling. They are based on the idea proposed by Santiago et al., which combines the randomized response technique proposed by Warner together with ranked set sampling. The authors will carry out a simulation study to compare the item count technique under ranked set sampling and under simple random sampling without replacement.

Bayesian Estimation ofWarner’s Randomized Response Technique with Transmuted Kumaraswamy Prior

In recent time, the Bayesian approach to randomized response technique has been used for estimating the population proportion especially of respondents possessing sensitive attributes such as induced abortion, tax evasion and shoplifting. This is done by combining suitable prior information about an unknown parameter of the population with the sample information for the estimation of the unknown parameter. In this study, possibility of using a transmuted Kumaraswamy prior is raised, yielding a new Bayes estimator for estimating population proportion of sensitive attribute for Warner’s randomized response technique. Consequently, the proposed Bayes estimator with transmuted Kumaraswamy prior is compared with existing Bayes estimators developed with a simple beta and Kumaraswamy priors in terms of their mean square error. The proposed estimator competes well with the existing estimators for some values of population proportion. The performances of Bayes estimators were also compared using some benchmark data.

Using the Randomized Response Technique to Investigate Illegal Fishing and Contribute to Abalone Management in Northern California

<p>Illegal fishing has detrimental environmental and social impacts, but these effects are difficult to mitigate without reliable estimates of fisher non-compliance. Methods used by fisheries managers to estimate illegal fishing often require indirect estimation of poaching using biological, economic, or sociological indicators. This study presents a unique application of the randomized response technique (RRT) for direct estimation of non-compliance in the Northern California recreational red abalone (Haliotis rufescens) fishery. Using an anonymous paper-based compliance and sociodemographic survey of recreational fishers in Sonoma and Mendocino Counties, I estimate 29% non-compliance with the daily take limit, 23% with the minimum size limit, 19% with licensing laws, and 15% with the annual take limit and among the general population. No significant relationship between the socio-demographic variables gathered (age, income, county of residence, fishing experience) and RRT survey responses indicates that no clear profile can be ascertained to help identify potential violators. However, visitors have higher non-compliance estimates for all regulations except daily take limits, for which an estimated 72% of locals violate vs. only 18% of visitors. These rule-specific violation estimates allow for the development of efficient management priorities, as managers may target specific measures or user groups. Further research should develop quantitative RRT estimates of illegal take, and explore violation drivers operating within the fisher population.</p>

Using the Randomized Response Technique to Investigate Illegal Fishing and Contribute to Abalone Management in Northern California

<p>Illegal fishing has detrimental environmental and social impacts, but these effects are difficult to mitigate without reliable estimates of fisher non-compliance. Methods used by fisheries managers to estimate illegal fishing often require indirect estimation of poaching using biological, economic, or sociological indicators. This study presents a unique application of the randomized response technique (RRT) for direct estimation of non-compliance in the Northern California recreational red abalone (Haliotis rufescens) fishery. Using an anonymous paper-based compliance and sociodemographic survey of recreational fishers in Sonoma and Mendocino Counties, I estimate 29% non-compliance with the daily take limit, 23% with the minimum size limit, 19% with licensing laws, and 15% with the annual take limit and among the general population. No significant relationship between the socio-demographic variables gathered (age, income, county of residence, fishing experience) and RRT survey responses indicates that no clear profile can be ascertained to help identify potential violators. However, visitors have higher non-compliance estimates for all regulations except daily take limits, for which an estimated 72% of locals violate vs. only 18% of visitors. These rule-specific violation estimates allow for the development of efficient management priorities, as managers may target specific measures or user groups. Further research should develop quantitative RRT estimates of illegal take, and explore violation drivers operating within the fisher population.</p>