  Many issues of interest to social scientists and policymakers are of a
sensitive nature in the sense that they are intrusive, stigmatizing or
incriminating to the respondent. This results in refusals to cooperate or
evasive cooperation in studies using self-reports. In a seminal article Warner
proposed to curb this problem by generating an artificial variability in
responses to inoculate the individual meaning of answers to sensitive
questions. This procedure was further developed and extended, and came to be
known as the randomized response (RR) technique. Here, we propose a unified
treatment for eliciting sensitive binary as well as quantitative information
with RR based on a model where the inoculating elements are provided for by the
randomization device. The procedure is simple and we will argue that its
implementation in a computer-assisted setting may have superior practical
capabilities.
