This paper examines the relation between the number of response categories used to measure attitudes in survey interviews and the reliability of such attitude measurements. I review and criticize the hypothesis that reliability increases with the "information carrying capacity" of a response scale. I also review the literature on the relationship between the number of scale points and measurement reliability. This leads to a set of predictions regarding the relationship between the number of scale points and reliability of measurement, which I then examine using results obtained from three-wave panel studies conducted by the General Social Survey and the National Election Study. Reliability estimates were obtained via several procedures (LISREL, EQS, and LISCOMP) employing a variety of statistical-estimation approaches: maximum likelihood (Jöreskog 1979), generalized least squares based on Browne's (1984) asymptotically distribution-free (ADF) approach, and estimation based on categorical variable methods (CVM) (Jöreskog 1990; Muthen 1984). With one important exception, reliability is generally higher for attitudes measured using more response categories. Reliability is relatively higher when attitudes are assessed using two-category rather than three-category response scales, but evidence consistently supports the view that for four or more category scales, reliability increases with the number of response categories, but at a decreasing rate. I also examine the hypothesis that reliability can be enhanced by combining three-category response forms with other types of questions to measure the direction and intensity of attitudes, i.e., via unfolding methods. Support for this hypothesis is lacking, but more research is necessary before firm conclusions can be drawn.