Fitting an ex-Gaussian function to examine costs in event-based prospective memory: evidence for a continuous
Shayne Loft1, Vanessa K Bowden1, B Hunter Ball2
1The University of Western Australia, Australia.
Abstract:
Event-based prospective memory (PM) tasks require individuals to remember to perform a deferred action when a target event occurs. PM task requirements can slow ongoing task responses on non-target trials ('costs') under conditions where the defining features of targets are non-focal to the ongoing task, which is indicative that individuals have allocated some form of cognitive control process to the PM task. Recent fits of the ex-Gaussian mathematical function to non-target trial response distributions by prior studies have indicated that these control processes are transiently allocated. In the current paper, fits of the ex-Gaussian function to data reported by Loft and Humphreys (2012) demonstrate a shift in the entire response time distribution (μ) and an increase in skew (τ) for a non-focal PM condition required to remember to make a PM response if presented with category exemplars, compared to a control condition. This change in μ is indicative of a more continuous PM monitoring profile than that reported by prior studies. In addition, within-subject variability in μ was reliably correlated with PM accuracy, suggesting that these control processes allocated on a regular basis were functional to PM accuracy. In contrast, when the ongoing task directed attention to the defining features of targets (focal PM) there was a trend level increase in μ, but the within-subject variability in μ was not correlated with PM accuracy, consistent with the theoretical premise that focal PM tasks are not as dependent on cognitive control as non-focal PM tasks.
Related Concept Videos
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Expected Frequencies in Goodness-of-Fit Tests
Determination of Expected Frequency


