Estimating the prevalence of sensitive behaviour and cheating with a dual design for direct questioning and randomized response

Applied Statistics (Impact Factor: 1.49). 08/2010; 59(4):723-736. DOI: 10.1111/j.1467-9876.2010.00720.x
Source: PubMed


Randomized response is a misclassification design to estimate the prevalence of sensitive behaviour. Respondents who do not follow the instructions of the design are considered to be cheating. A mixture model is proposed to estimate the prevalence of sensitive behaviour and cheating in the case of a dual sampling scheme with direct questioning and randomized response. The mixing weight is the probability of cheating, where cheating is modelled separately for direct questioning and randomized response. For Bayesian inference, Markov chain Monte Carlo sampling is applied to sample parameter values from the posterior. The model makes it possible to analyse dual sample scheme data in a unified way and to assess cheating for direct questions as well as for randomized response questions. The research is illustrated with randomized response data concerning violations of regulations for social benefit.

Download full-text


Available from: Peter G.M. van der Heijden
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: An advantage of randomised response and non-randomised models investigating sensitive issues arises from the characteristic that individual answers about discriminating behaviour cannot be linked to the individuals. This study proposed a new fuzzy response model coined 'Single Sample Count' (SSC) to estimate prevalence of discriminating or embarrassing behaviour in epidemiologic studies. The SSC was tested and compared to the established Forced Response (FR) model estimating Mephedrone use. Estimations from both SSC and FR were then corroborated with qualitative hair screening data. Volunteers (n = 318, mean age = 22.69 ± 5.87, 59.1% male) in a rural area in north Wales and a metropolitan area in England completed a questionnaire containing the SSC and FR in alternating order, and four questions canvassing opinions and beliefs regarding Mephedrone. Hair samples were screened for Mephedrone using a qualitative Liquid Chromatography-Mass Spectrometry method. The SSC algorithm improves upon the existing item count techniques by utilizing known population distributions and embeds the sensitive question among four unrelated innocuous questions with binomial distribution. Respondents are only asked to indicate how many without revealing which ones are true. The two probability models yielded similar estimates with the FR being between 2.6% - 15.0%; whereas the new SSC ranged between 0% - 10%. The six positive hair samples indicated that the prevalence rate in the sample was at least 4%. The close proximity of these estimates provides evidence to support the validity of the new SSC model. Using simulations, the recommended sample sizes as the function of the statistical power and expected prevalence rate were calculated. The main advantages of the SSC over other indirect methods are: simple administration, completion and calculation, maximum use of the data and good face validity for all respondents. Owing to the key feature that respondents are not required to answer the sensitive question directly, coupled with the absence of forced response or obvious self-protective response strategy, the SSC has the potential to cut across self-protective barriers more effectively than other estimation models. This elegantly simple, quick and effective method can be successfully employed in public health research investigating compromising behaviours.
    Full-text · Article · Aug 2011 · Substance Abuse Treatment Prevention and Policy
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Surveys on sensitive issues provide distorted prevalence estimates when participants fail to respond truthfully. The randomized-response technique (RRT) encourages more honest responding by adding random noise to responses, thereby removing any direct link between a participant's response and his or her true status with regard to a sensitive attribute. However, in spite of the increased confidentiality, some respondents still refuse to disclose sensitive attitudes or behaviors. To remedy this problem, we propose an extension of Mangat's (Journal of the Royal Statistical Society: Series B, 56, 93-95, 1994) variant of the RRT that allows for determining whether participants respond truthfully. This method offers the genuine advantage of providing undistorted prevalence estimates for sensitive attributes even if respondents fail to respond truthfully. We show how to implement the method using both closed-form equations and easily accessible free software for multinomial processing tree models. Moreover, we report the results of two survey experiments that provide evidence for the validity of our extension of Mangat's RRT approach.
    Full-text · Article · Aug 2011 · Behavior Research Methods
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The randomized-response technique (RRT) protects the privacy of respondents by adding random noise to their responses, such that there is no direct link between an individual's response and her true status. Although the RRT has repeatedly been shown to outperform direct questioning, it has rarely been used in survey research. First, it is difficult to survey multiple issues simultaneously. Second, traditional RRT models do not take the problem of nonadherence to the instructions into account. We describe a modification of the RRT that is capable of surveying multiple attributes using just a single randomization process and controls for nonadherence. An empirical application demonstrates the superiority of this approach over both, direct questioning and the forced-response variant of the RRT.
    Full-text · Article · Dec 2011 · International Journal of Public Opinion Research
Show more