Manipulating number generation: Loud + long = large?

Humans make numerous choices every day and tend to perceive these choices as free. The present study shows how simple free choices are biased by experiencing unrelated auditory information. In two experiments, participants categorized tones according to their intensity on the dimensions volume and duration on the majority of trials. On some trials, however, they were to randomly generate a number, and we found these choices to be influenced by tone intensity. Particularly, if participants were cued toward volume, loud tones clearly biased participants to generate larger numbers. For tone duration, a similar effect only emerged if spatial information was reinforced by the motor context of the task. The findings extend previous findings relating to the ATOM framework (A Theory of Magnitude) by an explicit focus on auditory magnitude processing. As such, they also constrain ATOM by showing that the connections between different magnitude dimensions vary to a considerable degree.     

Estimation of careless error and lucky guess probabilities for dichotomous test items: A psychometric application of a biometric latent class model with random effects

Medical research has extensively dealt with the estimation of the accuracy (sensitivity and specificity) of a diagnostic test for screening individuals. In this paper we apply the biometric latent class model with random effects by Qu, Tan, and Kutner [(1996). Random effects models in latent class analysis for evaluating accuracy of diagnostic tests. Biometrics, 52, 797-810] to estimate the response error (careless error and lucky guess) probabilities for dichotomous test items in the psychometric theory of knowledge spaces. The approach is illustrated with simulated data. In particular, we extend this approach to give a generalization of the basic local independence model in knowledge space theory. This allows for local dependence among the indicators given the knowledge state of an examinee and/or for the incorporation of covariates.     

Mimic automata: A novel formal model for mimic computing

In this paper, we aim to establish a mathematical model for mimic computing. To this end, we present a novel automaton called a mimic automaton. First, a one-dimensional cellular automaton is used for expressing some dynamic changes in the structure of a computing unit, a sequential automaton is employed to describe some state transitions, a hierarchical automaton is employed to express the different granularities of some computing units, and a probabilistic automaton is used to depict some random changes of a computing unit. Second, a mimic automaton is obtained by combining the various types of automata mentioned above in a certain logical relationship. Compared with the existing models of mimic computing, the new model portrays the operational semantics for a mimic computing system, and it can directly describe the behaviors of a system. Furthermore, the new model possesses a stronger generality.     

The role of the executive system in visuo-spatial memory functioning

Participants were presented with a spatial sequence in which between 4 and 10 cells were highlighted. On each trial list length was unknown to the participant who was required to serially recall the last four cells. Processing of longer lists is assumed to call upon the executive system, which is thought to be involved in updating the contents of the short-term visuo-spatial store. Study 1 revealed that loading the executive system with concurrent random letter generation impaired performance on the spatial task especially recall of the early serial positions. However, contrary to expectation the degree of impairment was no greater on the longer lists, where it had been assumed that updating would be occurring. Study 2 confirmed this finding and demonstrated that relative to sequences of known length, under conditions of uncertainty when the list length was unknown, spatial recall was impaired even on short sequences. The present results support the growing consensus, which is suggestive of closer links between visuo-spatial and executive processes. However, it remains unclear whether or not updating is actually occurring on the longer sequences, and if it is, what specific executive processes are involved.     

Evaluating three stuttering assessments through network analysis,random forests and cluster analysis

PurposeIn stuttering, cognitive and behavioural variables interact in nonlinear fashion. These variables can be assessed by instruments which evaluate perceived impact of stuttering and stuttering severity. We applied three statistical methods in combination to the analysis of three assessment protocols to discover relationships within and between the tests to better understand variations in behavioural and social aspects of stuttering.MethodsScores from Stuttering Severity Index (SSI-IV), Overall Assessment of the Speaker’s Experience of Stuttering scale (OASES), and Unhelpful Thoughts and Beliefs About Stuttering scale (UTBAS), collected from 26 participants were compared using three statistical methods: network analysis, random forests, and cluster analysis.ResultsNetwork analysis demonstrated that SSI-IV only weakly interacts with a quality of life index (OASES) and a self-perception and belief systems index (UTBAS). Random forest analyses revealed the last two measures relate strongly to each other. The results from cluster analysis suggest a) a possible regrouping of OASES items and b) a possible use of one UTBAS scale instead of the three.ConclusionA combination of three statistical methods allowed us to evaluate the three assessments in more depth. The lack of interaction between the SSI-IV on the one hand, and OASES and UTBAS on the other, suggests that the network of the three commonly used stuttering assessments may be fractured in a non-productive way. A potential gap may exist for an assessment tool that would link behavioural and social aspects of stuttering.     

Maintaining perceived control with unemployment facilitates future adjustment

Unemployment is a major challenge to individuals' development. An important personal resource to ameliorate the negative impact of unemployment may be perceived control, a general-purpose belief system. Little is known, however, about how perceived control itself changes with the experience of unemployment and what the antecedents, correlates, and consequences of such change in perceived control are in different ages. We use data from the German Socio-Economic Panel Study (N = 413 who experienced unemployment and N = 413 case-matched controls; time period of data collection: 1994–1996) to examine whether perceived control changes with unemployment, explore the role of socio-demographic, psychosocial and health factors in moderating such change, and investigate whether levels of perceived control prior to unemployment and unemployment-related change in perceived control predict unemployment-related outcomes up to five years following. Results indicated that, on average, perceived control remained relatively stable with unemployment, and that younger and older workers did not differ in this regard. However, there were sizeable individual differences in change in perceived control, with women and those with fewer years of education experiencing greater unemployment-related declines in perceived control. Lower levels of perceived control prior to unemployment and steeper unemployment-related decrements in perceived control were each associated with a higher risk of remaining unemployed in the 12 months immediately following unemployment. Steeper unemployment-related declines in perceived control also predicted lower life satisfaction up to five years following. We discuss possible pathways by which perceived control may facilitate adjustment to unemployment, consider the role of perceived control for better understanding the dynamics of unemployment, and suggest routes for further more process-oriented inquiry.     

Drinking patterns and drunk-driving behaviour in Catalonia,Spain: A comparative study

This study explores three alcohol-related databases so as to provide a comprehensive understanding of drinking patterns and the prevalence of alcohol-impaired driving in Catalonia (Spain). The rate of alcohol-impaired drivers is compared with the percentage of drinkers in this population, with a particular focus on heavy episodic drinkers. Two strategies adopted by law enforcement agents when conducting alcohol breath tests are examined: (i) non-random and (ii) random approaches to roadblock location and driver selection. We find that heavy drinker profiles (in terms of age and gender) closely match those of alcohol-impaired drivers detected at strategically located, non-random sobriety checkpoints (especially in the case of female drivers), and that they also correlate with the age-gender distribution of drivers involved in road accidents with victims. Different drink driving patterns are detected when sobriety checkpoints are located randomly and drivers are tested at random. Older drivers are identified as a risk group as they abandon the safer driving habits in relation to alcohol shown when they were middle-aged. A combination of non-random and random controls would increase driver perception of their chances of being detected when drink driving. As such, the whole population, regardless of their drinking profile, would be alerted to the serious personal, social and legal implications of alcohol-impaired driving.     

Religion and Science: What Is at Stake?

Abstract : “Religion and Science: What Is at Stake” looks at the latest information available on global warming from the International Panel on Climate Change and puts it in the context of the current culture war between progressives and conservatives. We worry that the science will become captive to ideological concerns that are theological, economic, and therefore political. The ideological domination of science may make a sustainable response to global warming even more difficult. It is vitally important that Christian theologians learn enough about the science to be articulate and support the scientists in their endeavors to promote our care of the creation.     

Detecting and predicting changes

When required to predict sequential events, such as random coin tosses or basketball free throws, people reliably use inappropriate strategies, such as inferring temporal structure when none is present. We investigate the ability of observers to predict sequential events in dynamically changing environments, where there is an opportunity to detect true temporal structure. In two experiments we demonstrate that participants often make correct statistical decisions when asked to infer the hidden state of the data generating process. However, when asked to make predictions about future outcomes, accuracy decreased even though normatively correct responses in the two tasks were identical. A particle filter model accounts for all data, describing performance in terms of a plausible psychological process. By varying the number of particles, and the prior belief about the probability of a change occurring in the data generating process, we were able to model most of the observed individual differences.