Variance jackknife estimation for randomized response surveys: A simulation study and an application to explore cheating in exams and bullying. Issue 3 (20th December 2019)

• Record Type: Journal Article
• Authors: Arnab, Raghunath; Cobo, Beatriz
• Is Part Of: Computational and mathematical methods. Volume 2:Issue 3(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-12-20
• Subjects: complex surveys -- randomized response -- resampling methods; Mathematics -- Data processing -- Periodicals; Numerical analysis -- Periodicals; Numerical analysis; Mathematics -- Data processing; Periodicals; 004.0151
• DOI: 10.1002/cmm4.1073
• Languages: English
• ISSNs: 2577-7408

Abstract

Abstract : The aim of the randomized response (RR) technique is to decrease social desirability bias, thus guaranteeing confidentiality, improving respondent cooperation, and obtaining reliable estimates. This technique obtains stronger estimates of sensitive characteristics, compared to direct questioning, by reducing respondents motivation to report falsely their attitudes. In this paper, we have considered the problem of estimation of variance of an estimator based on an RR survey data obtained from a complex survey design by using resampling techniques. The performance of the proposed jackknife modified estimator is tested by simulation studies. The simulation studies reveal that there is a decrease in the relative bias and the relative mean square error for all RR schemes. An RR survey was conducted to investigate sensitive behaviors such as cheating in exams and bullying. The application of the new jackknife confidence intervals revealed substantial increase in high‐tech cheating and bullying in the university campuses.