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.
