Sensitive Question Techniques and Careless Responding: Adjusting the Crosswise Model for Random Answers

Abstract

The crosswise model is a popular sensitive question technique often considered more accurate than direct questioning. When this technique is used, a sensitive question is paired with a nonsensitive question that has a known prevalence and respondents are asked to give a joint answer to the pair of questions. Recent research has shown that prevalence estimates based on the crosswise model are biased towards 50% when respondents answer randomly, and that random answers are frequent. I develop methods to adjust the crosswise model for self-reported random answers. Results from an exploratory online survey (n = 103) show that (i) fewer respondents report random answers than might be expected given unadjusted results, (ii) results differ considerably between questions, and (iii) one of three questions yields an estimate that is substantially and significantly above the true value even after adjusting for random answers.