Symmetric truth detection model: A randomized response approach

Abstract

When collecting sensitive information on abortion, drug addiction, examination dishonesty and tax evasion among others, many researchers use direct questioning which may not yield valid data. This is because respondents fear embarrassment and victimization. In this study we have formulated a Symmetric Truth Detection Model which uses two randomization devises to protect the privacy of respondents leading to a more honest response. This model is more efficient than the earlier models namely the Asymmetric Truth detection Models.