Although most survey researchers agree that reliability is a critical requirement for survey data, there have not been many efforts to assess the reliability of responses in national surveys. In addition, there are quite different approaches to studying the reliability of survey responses. In the first section of the Lecture, I contrast a psychological theory of over-time consistency with three statistical models that use reinterview data, multi-trait multi-method experiments, and three-wave panel data to estimate reliability. The more sophisticated statistical models reflect concerns about memory effects and the impact of method factors in reinterview studies. In the following section of the Lecture, I examine some of the major findings from the literature on reliability. Despite the differences across methods for exploring reliability, the findings mostly converge, identifying similar respondent and question characteristics as major determinants of reliability. The next section of the paper looks at the correlations among estimates of reliability derived from the different methods; it finds some support for the validity of the measures from traditional reinterview studies. The empirical claims motivating the more sophisticated methods for estimating reliability are not strongly supported in the literature. Reliability is, in my judgment, a neglected topic among survey researchers, and I hope the Lecture spurs further studies of the reliability of survey questions.