Algorithms for approximate Bayesian inference, such as those based on sampling (i.e., Monte Carlo methods), provide a natural source of models of how people may deal with uncertainty with limited cognitive resources. Here, we consider the idea that individual differences in working memory capacity (WMC) may be usefully modeled in terms of the…

Predictability of behavior is an important characteristic in many fields including biology, medicine, marketing, and education. When a sequence of actions performed by an individual can be modeled as a stationary time-homogeneous Markov chain the predictability of the individual's behavior can be quantified by the entropy rate of the process. This…

Although the experience of time is of central relevance for psychopathology, qualitative approaches to study the inner experience of time have been largely neglected in autism research. We present results from qualitative data acquired from 26 adults with high functioning autism spectrum disorder (ASD). Employing inductive content analysis we…

The combination of Qualitative Comparative Analysis (QCA) with process tracing, which we call set-theoretic multimethod research (MMR), is steadily becoming more popular in empirical research. Despite the fact that both methods have an elected affinity based on set theory, it is not obvious how a within-case method operating in a single case and a…

Through a sensitivity analysis, the analyst attempts to determine whether a conclusion of causal inference could be easily reversed by a plausible violation of an identification assumption. Analytic conclusions that are harder to alter by such a violation are expected to add a higher value to scientific knowledge about causality. This article…

Theory of mind is the understanding that other people have mental states that drive their actions and that those mental states can be different from one's own. Without understanding theory of mind and being able to take others' perspectives, it could be difficult for children to read and understand narrative texts. This paper posits that…

Statistical inference involves drawing scientifically-based conclusions describing natural processes or observable phenomena from datasets with intrinsic random variation. We designed, implemented, and validated a new portable randomization-based statistical inference infrastructure (http://socr.umich.edu/HTML5/Resampling_Webapp) that blends…

Theory of mind is the understanding that other people have mental states that drive their actions and that those mental states can be different from one's own. Without understanding theory of mind and being able to take others' perspectives, it could be difficult for children to read and understand narrative texts. This paper posits that…

Statisticians have made great progress in creating methods that reduce our reliance on parametric assumptions. However this explosion in research has resulted in a breadth of inferential strategies that both create opportunities for more reliable inference as well as complicate the choices that an applied researcher has to make and defend.…

Learning from expository science texts is challenging. These studies explore whether difficulties can be attributed to poor memory or poor reasoning. To eliminate the need for memory during testing, some students took the tests with the texts available. To test for the effects of reasoning on performance, some students were prompted to engage in…

Frequentists' inference often delivers point estimators associated with confidence intervals or sets for parameters of interest. Constructing the confidence intervals or sets requires understanding the sampling distributions of the point estimators, which, in many but not all cases, are related to asymptotic Normal distributions ensured by central…

While research has repeatedly found evidence that readers infer characters' emotions, we investigate three outstanding questions about the content and time course of such inferences. We ask whether even simple narratives give rise to emotion inferences, in what form such inferences are encoded into long-term memory, and whether they are uniquely…

A previous study has shown that children use recent input to adapt their syntactic predictions and use these adapted predictions to infer the meaning of novel words. In the current study, we investigated whether children could use this mechanism to disambiguate words whose interpretation as a noun or a verb is ambiguous. We tested 2- to 4-year-old…

Lexical inference strategy plays an important role in increasing the level of reading comprehension of second or foreign language learners. Lexical inferencing as an efficient strategy to deal with unfamiliar words has attracted much attention in the comprehension literature. However, few studies on lexical inferencing have been conducted in an…

We examine the challenges of teaching probability through the use of modelling. We argue how an integrated modelling approach might facilitate a coordinated understanding of distribution by marrying theoretical and data-oriented perspectives and present probability as more connected to the social lives of modern-day students. Research is, however,…