Simple Co‐Occurrence Statistics Reproducibly Predict Association Ratings

What determines human ratings of association? We planned this paper as a test for association strength (AS) that is derived from the log likelihood that two words co‐occur significantly more often together in sentences than is expected from their single word frequencies. We also investigated the moderately correlated interactions of word frequency, emotional valence, arousal, and imageability of both words (r's ≤ .3). In three studies, linear mixed effects models revealed that AS and valence reproducibly account for variance in the human ratings. To understand further correlated predictors, we conducted a hierarchical cluster analysis and examined the predictors of four clusters in competitive analyses: Only AS and word2vec skip‐gram cosine distances reproducibly accounted for variance in all three studies. The other predictors of the first cluster (number of common associates, (positive) point‐wise mutual information, and word2vec CBOW cosine) did not reproducibly explain further variance. The same was true for the second cluster (word frequency and arousal); the third cluster (emotional valence and imageability); and the fourth cluster (consisting of joint frequency only). Finally, we discuss emotional valence as an important dimension of semantic space. Our results suggest that a simple definition of syntagmatic word contiguity (AS) and a paradigmatic measure of semantic similarity (skip‐gram cosine) provide the most general performance‐independent explanation of association ratings.     

Bayesian PTSD-Trajectory Analysis with Informed Priors Based on a Systematic Literature Search and Expert Elicitation

There is a recent increase in interest of Bayesian analysis. However, little effort has been made thus far to directly incorporate background knowledge via the prior distribution into the analyses. This process might be especially useful in the context of latent growth mixture modeling when one or more of the latent groups are expected to be relatively small due to what we refer to as limited data. We argue that the use of Bayesian statistics has great advantages in limited data situations, but only if background knowledge can be incorporated into the analysis via prior distributions. We highlight these advantages through a data set including patients with burn injuries and analyze trajectories of posttraumatic stress symptoms using the Bayesian framework following the steps of the WAMBS-checklist. In the included example, we illustrate how to obtain background information using previous literature based on a systematic literature search and by using expert knowledge. Finally, we show how to translate this knowledge into prior distributions and we illustrate the importance of conducting a prior sensitivity analysis. Although our example is from the trauma field, the techniques we illustrate can be applied to any field.     

A tutorial on Bayes factor estimation with the product space method

The Bayes factor is an intuitive and principled model selection tool from Bayesian statistics. The Bayes factor quantifies the relative likelihood of the observed data under two competing models, and as such, it measures the evidence that the data provides for one model versus the other. Unfortunately, computation of the Bayes factor often requires sampling-based procedures that are not trivial to implement. In this tutorial, we explain and illustrate the use of one such procedure, known as the product space method (Carlin & Chib, 1995). This is a transdimensional Markov chain Monte Carlo method requiring the construction of a “supermodel” encompassing the models under consideration. A model index measures the proportion of times that either model is visited to account for the observed data. This proportion can then be transformed to yield a Bayes factor. We discuss the theory behind the product space method and illustrate, by means of applied examples from psychological research, how the method can be implemented in practice.     

Exploring Directional Consistency in Offending: The Case of Residential Burglary in The Hague

Many aspects of human behaviour are remarkably stable across times, places and situations. Repetition and predictability also characterises our geographical behaviour. Prior research has confirmed that criminal behaviour is no exception. Offenders tend to recidivate, and recidivists tend to be behaviourally consistent in many aspects, including geographical ones. The present study assesses directional consistency in offending. It reviews the literature on directional consistency. It proposes an improved measure of directional consistency, and empirically uses this measure to explore directional consistency amongst a set of 268 burglars in The Hague. Copyright © 2012 John Wiley & Sons, Ltd.     

An application of Carnapian inductive logic to an argument in the philosophy of statistics

I claim that an argument from the philosophy of statistics can be improved by using Carnapian inductive logic. Gelman and Shalizi [9] criticise a philosophical account of how statisticians ought to choose statistical models which they call ‘the received view of Bayesian inference’ and propose a different account inspired by falsificationist philosophy of science. I introduce another philosophical account inspired by Carnapian inductive logic and argue that it is even better than Gelman and Shalizi's falsificationist account.     

心理与教育统计学之有效学习策略探析

研究目的在于探讨学习初等统计学之有效学习策略.研究对象为修习心理与教育统计学的学生50人.研究工具为统计学期中与期末测验、学习策略量表以及半结构式访谈大纲.学生于期中与期末测验所测得的能力值透过共同题等化,作为统计学的学习表现.学习策略量表改编自过去已发表的研究工具.结果发现,期中认知策略得分与期末学习表现有相关;而期中学习表现则与期末认知策略得分、期末学习表现均有相关.从质性数据获悉,研读原文书、积极投入Moodle预习测验与教科书提供的在线测验、做笔记、和同学相互讨论以及考试前妥善准备,都是有效且可行的认知策略.     

Performance breakdown effects dissociate from error detection effects in typing

Mistakes in skilled performance are often observed to be slower than correct actions. This error slowing has been associated with cognitive control processes involved in performance monitoring and error detection. A limited literature on skilled actions, however, suggests that preerror actions may also be slower than accurate actions. This contrasts with findings from unskilled, discrete trial tasks, where preerror performance is usually faster than accurate performance. We tested 3 predictions about error-related behavioural changes in continuous typing performance. We asked participants to type 100 sentences without visual feedback. We found that (a) performance before errors was no different in speed than that before correct key-presses, (b) error and posterror key-presses were slower than matched correct key-presses, and (c) errors were preceded by greater variability in speed than were matched correct key-presses. Our results suggest that errors are preceded by a behavioural signature, which may indicate breakdown of fluid cognition, and that the effects of error detection on performance (error and posterror slowing) can be dissociated from breakdown effects (preerror increase in variability).     

Outline of a Physico-Mathematical Theory of the Brain

The author comments on the (mis?)portrayal of her research in an article by Brand and Bradley (2012).     

Performance reactivity in a continuous-performance task: Implications for understanding post-error behavior

Although there has been considerable interest in the effects of errors on subsequent performance, relatively few studies have considered the effects of non-error events that contain some performance-relevant information, such as correct performance on critical trials. In the present article, we propose and assess a hypothesis of performance reactivity. In support of this hypothesis, we provide evidence of performance decrements following both incorrect and correct responses but not following performance-irrelevant events. More specifically, in a continuous response task (Sustained Attention to Response Task), we (1) replicate previous findings that errors of commission on rare NOGO trials produce decrements in subsequent performance, and (2) observe that correct withholds to NOGO trials produce decrements in subsequent accuracy relative to task-irrelevant tones. These results corroborate a hypothesis that some error-related effects on subsequent performance are not unique, but are instead a particularly salient version of a more general performance-reactivity effect.     

Episodes of momentary resilience in daily life are associated with HRV reductions to stressful operations in firefighters: an ambulatory assessment approach using bayesian multilevel modeling

ABSTRACT

Background: Resilience is discussed to constitute a protective buffer against stress, thus fostering health. Methods: This study aimed to assess resilience both via traditional questionnaire and in everyday life on a momentary basis, and to relate these measures to autonomic functioning (heart rate variability, HRV) in 38 male firefighters during a weekday. Stressful operations, non-stressful operations and routine work at the firestation were coded during 24 hours. Momentary negative affect, feelings of resilience, and HRV were recorded via ecological momentary assessment. Findings: Questionnaire-assessed resilience was significantly positively associated with aggregated momentary resilience (r = .58, p < .001), but unrelated to HRV. However, controlling for multiple confounders (e.g., age, smoking, bodily movement, waist-to-height ratio) momentary resilience was associated with attenuated HRV and lower negative affect during stressful encounters only. Discussion: The findings suggest that momentary feelings of resilience are accompanied by vagal withdrawal to stress, possibly indicating psychological flexibility and adaptive responding to stress.