The Robustness and Applicability of Speed-Accuracy Decomposition, a Technique for Measuring Partial Information

Abstract

Speed-accuracy decomposition (SAD) is a relatively new technique for studying the time course of information processing. It uses information on both the temporal distributions and the accuracies of participants' responses to two types of trials to derive an estimate of the amount of partial information available to participants at specific points in processing. As a new technique, its range of applicability and robustness have not yet been fully determined. Simulations are reported here that investigate these issues, with simulated data sets, SAD analysis of same, and comparison of the SAD analysis results to the parameters used to generate the data. In general, SAD appears to be reasonably robust against certain violations of assumptions and a variety of unusual data patterns. It is recommended that future SAD studies be accompanied by simulations based on observed parameters to better understand the data obtained.