Australasian Mathematical Psychology Conference 2019

Converting continuous tracking data to response time distributions

Alexander Thorpe
Ami Eidels
University of Newcastle
Keith Nesbitt
University of Newcastle
Rachel Heath
University of Newcastle

Experimental methodologies used in cognitive science typically employ trial-by-trial designs. However, many real-world behaviours of interest, such as driving, require continuous monitoring of information and often ongoing responses. In these case, there is no start and end to a trial, and the researcher cannot measure RT, preempting many successful approaches to analysis of RT data (Systems Factorial Technology and others). We present a novel technique for converting continuous tracking data to a trial-like form. Thirty-seven participants completed a continuous tracking task with two levels of task load. We calculated the absolute tracking error, which is the distance between the user-controlled needle and to-be-tracked target. We then converted these data to pseudo RTs by setting a threshold of maximum acceptable tracking error, identifying points in the time series when tracking error crossed this threshold, and calculating the time taken to return to acceptable performance. Analyses of mean (pseudo) RTs agreed with equivalent analyses of mean tracking error, albeit with less sensitivity. Our technique may allow researchers to apply established methodologies to previously unstudied phenomena, without collecting additional data or altering experimental designs.