684 – Collecting and Analyzing Sensitive Data: Making Lies Naked!
Estimation of Odds Ratio and Attributable Risk Using Randomized Response Techniques
Cheonsig Lee
Coastal Bend College
Stephen Sedory
Texas A&M University at Kingsville
Sarjinder Singh
Texas A&M University at Kingsville
In this paper, we first define odds ratio and attributable risk while considering investigating two sensitive attributes in real practice. Then we define two estimators of odds ratio and two estimators of attributable risk based data collected either using the simple model or crossed model proposed by Lee, Sedory and Singh (2013). We derive expressions for biases and variances of the resultant estimators. We investigate the performance of crossed model over the simple model under the same choice of parameters as discussed in Lee et al. (2013). Also the values of the odds ratio and attributable risk are reported based on a real data set.