Piéron's Law holds during stroop conflict: insights into the architecture of decision making

Piéron's Law describes the relationship between stimulus intensity and reaction time. Previously (Stafford & Gurney, 2004), we have shown that Piéron's Law is a necessary consequence of rise-to-threshold decision making and thus will arise from optimal simple decision-making algorithms (e.g., Bogacz, Brown, Moehlis, Holmes, & Cohen, 2006). Here, we manipulate the color saturation of a Stroop stimulus. Our results show that Piéron's Law holds for color intensity and color-naming reaction time, extending the domain of this law, in line with our suggestion of the generality of the processes that can give rise to Piéron's Law. In addition, we find that Stroop condition does not interact with the effect of color saturation; Stroop interference and facilitation remain constant at all levels of color saturation. An analysis demonstrates that this result cannot be accounted for by single-stage decision-making algorithms which combine all the evidence pertaining to a decision into a common metric. This shows that human decision making is not information-optimal and suggests that the generalization of current models of simple perceptual decision making to more complex decisions is not straightforward.     

Radical Semantics: A New Theory of Meaning

This paper extends Parikh’s earlier work in semantics with games of partial information and attempts to derive and represent the full content of an utterance from first principles. It also discusses various ways in which this content may be indeterminate.     

Can Constructive Mathematics be Applied in Physics?

The nature of modern constructive mathematics, and its applications, actual and potential, to classical and quantum physics, are discussed.     

A scale-invariant treatment for recursive path models

A reparameterization is formulated that yields estimates of scale-invariant parameters in recursive path models with latent variables, and (asymptotically) correct standard errors, without the use of constrained optimization. The method is based on the logical structure of the reticular action model.     

Equality and Monodic First-Order Temporal Logic

It has been shown recently that monodic first-order temporal logic without functional symbols but with equality is incomplete, i.e., the set of the valid formulae of this logic is not recursively enumerable. In this paper we show that an even simpler fragment consisting of monodic monadic two-variable formulae is not recursively enumerable.     

Recursive Partitioning to Identify Potential Causes of Differential Item Functioning in Cross-National Data

Differential item functioning (DIF) assessment is key in score validation. When DIF is present scores may not accurately reflect the construct of interest for some groups of examinees, leading to incorrect conclusions from the scores. Given rising immigration, and the increased reliance of educational policymakers on cross-national assessments such as Programme for International Student Assessment, Trends in International Mathematics and Science Study, and Progress in International Reading Literacy Study (PIRLS), DIF with regard to native language is of particular interest in this context. However, given differences in language and cultures, assuming similar cross-national DIF may lead to mistaken assumptions about the impact of immigration status, and native language on test performance. The purpose of this study was to use model-based recursive partitioning (MBRP) to investigate uniform DIF in PIRLS items across European nations. Results demonstrated that DIF based on mother's language was present for several items on a PIRLS assessment, but that the patterns of DIF were not the same across all nations.     

Recursive Partitioning with Nonlinear Models of Change

In this article, we introduce nonlinear longitudinal recursive partitioning (nLRP) and the R package longRpart2 to carry out the analysis. This method implements recursive partitioning (also known as decision trees) in order to split data based on individual- (i.e., cluster) level covariates with the goal of predicting differences in nonlinear longitudinal trajectories. At each node, a user-specified linear or nonlinear mixed-effects model is estimated. This method is an extension of Abdolell et al.'s (2002) longitudinal recursive partitioning while permitting a nonlinear mixed-effects model in addition to a linear mixed-effects model in each node. We give an overview of recursive partitioning, nonlinear mixed-effects models for longitudinal data, describe nLRP, and illustrate its use with empirical data from the Early Childhood Longitudinal Study—Kindergarten Cohort.     

Here Today,Gone Tomorrow? Assessing How Timing and Repetition of Scandal Information Affects Candidate Evaluations

Scholars and political consultants alike know that during a campaign even the hint of a scandal has the potential to distract from a candidate's policy messages—or even worse—can have dire consequences on Election Day. But does it matter whether the scandal breaks early as opposed to late in the campaign? And how do citizens respond when the scandal drags on for weeks? This study represents the first effort to shed light on these temporal dynamics. Results reveal that timing affects the immediate impact of scandal information, the rate at which those initial effects decay, and candidate evaluations offered at the campaign's conclusion. Additionally, I develop two competing hypotheses regarding how citizens may process scandal information when it is repeated throughout a campaign. Empirical tests suggest that voters eventually reach a saturation threshold after which additional repetition of scandal information has negligible effects on evaluations unless new details are a prominent feature of ongoing coverage, in which case repetition can extend the negative effects of scandal.