Literature DB >> 31124400

Estimating the dependence of mixed sensitive response types in randomized response technique.

Amanda My Chu1, Mike Kp So2, Thomas Wc Chan2, Agnes Tiwari3,4.   

Abstract

Sensitive questions are often involved in healthcare or medical survey research. Much empirical evidence has shown that the randomized response technique is useful for the collection of truthful responses. However, few studies have discussed methods to estimate the dependence of sensitive responses of multiple types. This study aims to fill that gap by considering a method based on moment estimation and without using the joint distribution of the responses. In addition to the construction of a covariance matrix for the multiple sensitive questions despite incomplete information due to the randomized response technique design, we can calculate the conditional mean of continuous sensitive responses given as categorical responses and partial correlations among continuous sensitive responses. We conduct a simulation experiment to study the bias and variance of the moment estimator with various sample sizes. We apply the proposed method in a healthcare study of the dependence structure among the responses of a survey concerning health and pressure on college students.

Keywords:  Data privacy; mixed-type questions; randomized responses; sensitive questions; unrelated question design

Mesh:

Year:  2019        PMID: 31124400     DOI: 10.1177/0962280219847492

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  2 in total

1.  An Empirical Study of Applying Statistical Disclosure Control Methods to Public Health Research.

Authors:  Amanda M Y Chu; Benson S Y Lam; Agnes Tiwari; Mike K P So
Journal:  Int J Environ Res Public Health       Date:  2019-11-15       Impact factor: 3.390

2.  Learning from work-from-home issues during the COVID-19 pandemic: Balance speaks louder than words.

Authors:  Amanda M Y Chu; Thomas W C Chan; Mike K P So
Journal:  PLoS One       Date:  2022-01-13       Impact factor: 3.240

  2 in total

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