Fitting the ex-Gaussian equation to reaction time distributions

Dawson, Michael R. W.

doi:10.3758/bf03202603

Cited by 65 publications

(45 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, we would expect noncumulative latency distributions to be described well by the theoretical distribution that describes just such a process: the exGaussian (cf. Burbeck & Luce, 1982;Dawson, 1988; ponentially (or, as described above, accumulates exponentially, as derived in Appendix B).…”

Section: Latency Distributionsmentioning

confidence: 99%

An analysis of latency and interresponse time in free recall

1994

View full text Add to dashboard Cite

In four experiments, subjects freely recalled previously studied items while a voice key and computer recorded each item's recall latency relative to the onset of the recall period. The measures of recall probability and mean recall latency were shown to be empirically independent, demonstrating that there exists no a priori relationship between the two. In all four experiments, latency distributions were fit well by the ex-Gaussian, suggesting that retrieval includes a brief normally distributed initiation stage followed by a longer exponentially distributed search stage. Further, the variation in mean latency stemmed from the variation in the duration of the search stage, not the initiation stage. Interresponse times (IRTs), the time elapsed between two successive item recalls, were analyzed as well. The growth of mean IRTs, plotted as a function of output position, was shown to be a simple function of the number of items not yet recalled. Finally, the mathematical nature of both free recall latency and IRT growth are shown to be consistent with a simple theoretical account of retrieval that depicts mean recall latency as a measure of the breadth of search. 511Perhaps the most striking feature of episodic free recall is the distinctively long pause that sometimes precedes a response. Even a study list with only a few items often results in response latencies greater than 10 sec. These lengthy response times are unique to free recall, as cued recall and recognition typically yield response times of 1 or 2 sec. Yet although analyses of cued recall latency (e.g., MacLeod & Nelson, 1984) or recognition latency (e.g., Hockley, 1982) are quite common, few investigators have measured free recall latency, the time elapsed from the onset of the recall period to the recall of an item, or interresponse times (IRTs), the time between consecutive retrievals.The limited attention given to either temporal measure may stem from the belief that recall probability and recall latency are a priori inversely related and therefore redundant measures. That is, an experimental manipulation that weakens the memory trace and thereby reduces recall probability should necessarily increase recall latency as well. Ifthis were the case, researchers could simply ignore free recall latency without overlooking any important information. Although such negative correlations can occur, there is no prior evidence that they either must (or even usually) occur. Indeed, three experiments in the present investigation yielded correlations between recall probability and latency that were negative, nonexistent, This research was supported in part by NIMH Training Grant MH-14268 to the first author. We thank Mari Chernow for her assistance in the laboratory and Bennet Murdock, Jeroen Raaijmakers, Richard Shiffrin, and Geoffrey Loftus for their comments. Correspondence concerning this article, as well as requests for raw data, should be addressed to D. Rohrer, Department of Psychology 0 I09, University of California at San Diego, La Jolla, CA 92093. and po...

show abstract

Section: Latency Distributionsmentioning

confidence: 99%

An analysis of latency and interresponse time in free recall

1994

View full text Add to dashboard Cite

show abstract

“…From a formal and computationalpoint of view, these models are often less demanding, and their application to data sets is a standard routine (cf. Cousineau & Larochelle, 1997;Dawson, 1988;Heathcote, 1996). A prominent example of this class of descriptive RT models is the "exGaussian" model, originally described by Hohle (1965).…”

mentioning

confidence: 99%

The ex-Wald distribution as a descriptive model of response times

Schwarz

2001

Behavior Research Methods, Instruments, & Computers

103

105

View full text Add to dashboard Cite

We propose a new quantitative model of response times (RTs) that combines some advantages of substantive, process-oriented models and descriptive, statistically oriented accounts. The ex-Wald model assumes that RT may be represented as a convolution of an exponential and a Wald-distributed random variable. The model accounts well for the skew, shape, and hazard function of typical RT distributions. The model is based on two broad information-processing concepts: (1) a data-driven processing rate describing the speed of information accumulation, and (2) strategic response criterion setting. These concepts allow for principled expectations about how experimental factors such as stimulus saliency or response probability might influence RT on a distributional level. We present a factorial experiment involving mental digit comparisons to illustrate the application of the model, and to explain how substantive hypotheses about selective factor effects can be tested via likelihood ratio tests.

show abstract

“…Assuming that motor errors are symmetric in time (Dawson 1988), the optimal time to release the ball (T dec ) would be the middle of any contiguous period in which the ball would land in the bucket (e.g., L(t) = 1). If there were two contiguous periods of success, 3 we assumed that participants would be probabilistically more likely to choose the release point with the shorter vertical distance between the ball and the bucket (for a similar reason that we assume that uncertainty accumulates over vertical distance in the catching task).…”

Section: Models Of Physical Reasoningmentioning

confidence: 99%

Different Physical Intuitions Exist Between Tasks, Not Domains

2018

View full text Add to dashboard Cite

Does human behavior exploit deep and accurate knowledge about how the world works, or does it rely on shallow and often inaccurate heuristics? This fundamental question is rooted in a classic dichotomy in psychology: human intuitions about even simple scenarios can be poor, yet their behaviors can exceed the capabilities of even the most advanced machines. One domain where such a dichotomy has classically been demonstrated is intuitive physics. Here we demonstrate that this dichotomy is rooted in how physical knowledge is measured: extrapolation of ballistic motion is idiosyncratic and erroneous when people draw the trajectories but consistent with accurate physical inferences under uncertainty when people use the same trajectories to catch a ball or release it to hit a target. Our results suggest that the contrast between rich and calibrated versus poor and inaccurate patterns of physical reasoning exists as a result of using different systems of knowledge across tasks, rather than being driven solely by a universal system of knowledge that is inconsistent across physical principles.

show abstract

Fitting the ex-Gaussian equation to reaction time distributions

Cited by 65 publications

References 9 publications

An analysis of latency and interresponse time in free recall

An analysis of latency and interresponse time in free recall

The ex-Wald distribution as a descriptive model of response times

Different Physical Intuitions Exist Between Tasks, Not Domains

Contact Info

Product

Resources

About