Performance measures, such as the critical success index (CSI or threat score), are widely used as summary measures of forecast quality. However, the sensitivity of these measures to aspects of forecast quality is not well understood. In this paper, we will examine the sensitivity of several measures of forecast quality, such as the CSI, equitable threat score, and true skill statistic, to changes in bias error for a hypothetical forecasting situation. The forecast situation is modelled through circular areas of observed and forecast events, such as precipitation greater than a threshold. The circles are separated by a given distance, and the radius of the observed circle is held fixed. The bias error is modelled by varying the radius of the forecast circle, and the aforementioned performance measures are computed. The sensitivity of these measures to bias error will be presented at the conference along with a discussion on the implications for interpreting verification information using these measures of performance.