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      ExGUtils: A python package for statistical analysis with the ex-gaussian probability density

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          Abstract

          The study of reaction times and their underlying cognitive processes is an important field in Psychology. Reaction times are usually modeled through the ex-Gaussian distribution, because it provides a good fit to multiple empirical data. The complexity of this distribution makes the use of computational tools an essential element in the field. Therefore, there is a strong need for efficient and versatile computational tools for the research in this area. In this manuscript we discuss some mathematical details of the ex-Gaussian distribution and apply the ExGUtils package, a set of functions and numerical tools, programmed for python, developed for numerical analysis of data involving the ex-Gaussian probability density. In order to validate the package, we present an extensive analysis of fits obtained with it, discuss advantages and differences between the least squares and maximum likelihood methods and quantitatively evaluate the goodness of the obtained fits (which is usually an overlooked point in most literature in the area). The analysis done allows one to identify outliers in the empirical datasets and criteriously determine if there is a need for data trimming and at which points it should be done.

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          Most cited references12

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          High-speed scanning in human memory.

          When subjects judge whether a test symbol is contained in a short memorized sequence of symbols, their mean reaction-time increases linearly with the length of the sequence. The linearity and slope of the function imply the existence of an internal serial-comparison process whose average rate is between 25 and 30 symbols per second.
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            Mean response times, variability, and skew in the responding of ADHD children: a response time distributional approach.

            Response time (RT) distributions from three fixed foreperiod conditions (2, 4, and 8 s) in a warned four-choice RT task were obtained for a group of boys with attention-deficit/hyperactivity disorder, combined type (ADHD; n = 17) and for two groups of normal control boys (age-matched, n = 18, and younger-aged, n = 10). Quantitative measures of distributional shape were derived by fitting the ex-Gaussian distributional model to the individual RT data. Statistical results indicate that the ADHD distributions differ from the age-matched control distributions with respect to the size of the tail (larger for the ADHD boys), but differ from the younger control distributions with respect to the location of the leading edge (slower for the younger control boys). Receiver operating characteristic (ROC) results reveal that the ex-Gaussian exponential component is highly diagnostic of the ADHD boys.
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              Drifting from slow to "D'oh!": working memory capacity and mind wandering predict extreme reaction times and executive control errors.

              A combined experimental, individual-differences, and thought-sampling study tested the predictions of executive attention (e.g., Engle & Kane, 2004) and coordinative binding (e.g., Oberauer, Süβ, Wilhelm, & Sander, 2007) theories of working memory capacity (WMC). We assessed 288 subjects' WMC and their performance and mind-wandering rates during a sustained-attention task; subjects completed either a go/no-go version requiring executive control over habit or a vigilance version that did not. We further combined the data with those from McVay and Kane (2009) to (1) gauge the contributions of WMC and attentional lapses to the worst performance rule and the tail, or τ parameter, of reaction time (RT) distributions; (2) assess which parameters from a quantitative evidence-accumulation RT model were predicted by WMC and mind-wandering reports; and (3) consider intrasubject RT patterns--particularly, speeding--as potential objective markers of mind wandering. We found that WMC predicted action and thought control in only some conditions, that attentional lapses (indicated by task-unrelated-thought reports and drift-rate variability in evidence accumulation) contributed to τ, performance accuracy, and WMC's association with them and that mind-wandering experiences were not predicted by trial-to-trial RT changes, and so they cannot always be inferred from objective performance measures. (c) 2012 APA, all rights reserved.
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                Author and article information

                Journal
                18 July 2017
                Article
                1707.05759
                5c270f2c-48f0-4e64-8696-170216b194a4

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                Custom metadata
                18 pages, 4 figures, 5 Tables
                stat.AP

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