Combining Speed and Accuracy into a Global Measure of Performance

Response time and accuracy are two of the most frequently collected dependent measures. Tradeoffs between speed and accuracy are often observed, both between people, and between experimental conditions. In this paper we consider how speed, and accuracy, can be combined into a single, overall measure of performance. We consider two different approaches that adjust accuracy scores based on observed speed of responding and we examine how well those measures work with different data sets. We then present a third approach that combines standardized speed and accuracy scores. We show how this latter approach can represent the data fairly well regardless of which (if any) speed-accuracy tradeoff occurs in the data. We also show how this measure can be further generalized by applying differential weightings to the standardized scores of speed, and accuracy, respectively. We conclude by discussing the value of the measure for use in analyzing human performance data where continuous indicators of accuracy or error can be collected or constructed relatively easily. Our goal in developing the global measure of performance is not to accurately model the speed-accuracy relationship, but rather to create a measure that is more sensitive to experimental differences and causal relationships than either speed or accuracy alone.