Answers to sensitive questions are prone to social desirability bias. If not properly addressed, the validity of the research can be suspect. This article presents multigroup item randomized response theory (MIRRT) to measure self-reported sensitive topics across cultures. The method was specifically developed to reduce social desirability bias by making an a priori change in the design of the survey. The change involves the use of a randomization device (e.g., a die) that preserves participants' privacy at the item level. In cases where multiple items measure a higher level theoretical construct, the researcher could still make inferences at the individual level. The method can correct for under- and overreporting, even if both occur in a sample of individuals or across nations. We present and illustrate MIRRT in a nontechnical manner, provide WinBugs software code so that researchers can directly implement it, and present 2 cross-national studies in which it was applied. The first study compared nonstudent samples from 2 countries (total n = 927) on permissive sexual attitudes and risky sexual behavior and related these to individual-level characteristics such as the Big Five personality traits. The second study compared nonstudent samples from 17 countries (total n = 6,195) on risky sexual behavior and related these to individual-level characteristics, such as gender and age, and to country-level characteristics, such as sex ratio.