Bayesian randomized response technique with multiple sensitive attributes: The case of information systems resource misuse

Ray S. W. CHUNG, Man Ying Amanda CHU, Mike K. P. SO

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The randomized response technique (RRT) is a classical and effective method used to mitigate the distortion arising from dishonest answers. The traditional RRT usually focuses on the case of a single sensitive attribute, and discussion of the case of multiple sensitive attributes is limited. Here, we study a business case to identify some individual and organizational determinants driving information systems (IS) resource misuse in the workplace. People who actually engage in IS resource misuse are probably not willing to provide honest answers, given the sensitivity of the topic. Yet, to develop the causal relationship between IS resource misuse and its determinants, a version of the RRT for multivariate analysis is required. To implement the RRT with multiple sensitive attributes, we propose a Bayesian approach for estimating covariance matrices with incomplete information (resulting from the randomization procedure in the RRT case). The proposed approach (i) accommodates the positive definite condition and other intrinsic parameter constraints in the posterior to improve statistical precision, (ii) incorporates Bayesian shrinkage estimation for covariance matrices despite incomplete information, and (iii) adopts a quasi-likelihood method to achieve Bayesian semiparametric inference for enhancing flexibility. We show the effectiveness of the proposed method in a simulation study. We also apply the Bayesian RRT method and structural equation modeling to identify the causal relationship between IS resource misuse and its determinants. Copyright © 2018 Institute of Mathematical Statistics.
Original languageEnglish
Pages (from-to)1969-1992
JournalAnnals of Applied Statistics
Volume12
Issue number3
Early online dateSep 2018
DOIs
Publication statusPublished - 2018

Fingerprint

Randomized Response Technique
Information Systems
Information systems
Attribute
Resources
Covariance matrix
Determinant
Incomplete Information
Semiparametric Inference
Shrinkage Estimation
Quasi-likelihood
Structural Equation Modeling
Likelihood Methods
Multivariate Analysis
Bayesian Estimation
Randomisation
Bayesian Approach
Positive definite
Flexibility
Simulation Study

Bibliographical note

Chung, R. S. W., Chu, A. M. Y., & So, M. K. P. (2018). Bayesian randomized response technique with multiple sensitive attributes: The case of information systems resource misuse. Annals of Applied Statistics, 12(3), 1969-1992. doi: 10.1214/18-AOAS1139

Keywords

  • Causal modeling
  • Markov chain Monte Carlo
  • Quasi-likelihood
  • Sensitive responses
  • Shrinkage estimation of covariance matrix
  • Unrelated question design