Bayesian estimation and testing of structural equation models

The Gibbs sampler can be used to obtain samples of arbitrary size from the posterior distribution over the parameters of a structural equation model (SEM) given covariance data and a prior distribution over the parameters. Point estimates, standard deviations and interval estimates for the parameters can be computed from these samples. If the prior distribution over the parameters is uninformative, the posterior is proportional to the likelihood, and asymptotically the inferences based on the Gibbs sample are the same as those based on the maximum likelihood solution, for example, output from LISREL or EQS. In small samples, however, the likelihood surface is not Gaussian and in some cases contains local maxima. Nevertheless, the Gibbs sample comes from the correct posterior distribution over the parameters regardless of the sample size and the shape of the likelihood surface. With an informative prior distribution over the parameters, the posterior can be used to make inferences about the parameters underidentified models, as we illustrate on a simple errors-in-variables model.We thank David Spiegelhalter for suggesting applying the Gibbs sampler to structural equation models to the first author at a 1994 workshop in Wiesbaden. We thank Ulf Böckenholt, Chris Meek, Marijtje van Duijn, Clark Glymour, Ivo Molenaar, Steve Klepper, Thomas Richardson, Teddy Seidenfeld, and Tom Snijders for helpful discussions, mathematical advice, and critiques of earlier drafts of this paper.     

Latent profile analysis of working memory capacity and thinking styles in adults and adolescents

This study of adults (n = 269) and adolescents (n = 308) applied latent profile analysis to preference for rational and/or experiential cognition, coupled with working memory capacity (WMC). A 4-profile solution comprising rationally dominant, experientially dominant, dual preference, and disengaged groups was retained for both adult and adolescent samples. Our solution indicated that high WMC was associated with both preference and ability to engage in rational processing. Profile membership significantly discriminated both adults and adolescents on several reasoning tasks and measures of cognitive biases. Overall our results indicate that cognitive processing styles and WMC can be combined to create a typology that distinguishes between four types of thinkers who significantly differ in their performance on reasoning tasks.     

A rational analysis of the acquisition of multisensory representations

How do people learn multisensory, or amodal, representations, and what consequences do these representations have for perceptual performance? We address this question by performing a rational analysis of the problem of learning multisensory representations. This analysis makes use of a Bayesian nonparametric model that acquires latent multisensory features that optimally explain the unisensory features arising in individual sensory modalities. The model qualitatively accounts for several important aspects of multisensory perception: (a) it integrates information from multiple sensory sources in such a way that it leads to superior performances in, for example, categorization tasks; (b) its performances suggest that multisensory training leads to better learning than unisensory training, even when testing is conducted in unisensory conditions; (c) its multisensory representations are modality invariant; and (d) it predicts ‘‘missing” sensory representations in modalities when the input to those modalities is absent. Our rational analysis indicates that all of these aspects emerge as part of the optimal solution to the problem of learning to represent complex multisensory environments.     

Can you tickle yourself if you swap bodies with someone else?

The effect of the body transfer illusion on the perceived strength of self- and externally-generated “tickle” sensations was investigated. As expected, externally generated movement produced significantly higher ratings of tickliness than those associated with self-generated movements. Surprisingly, the body transfer illusion had no influence on the ratings of tickliness, suggesting that highly surprising, and therefore hard to predict, experiences of body image and first-person perspective do not abolish the attenuation of tickle sensations. In addition, evidence was found that a version of the rubber hand illusion exists within the body transfer illusion. We situate our findings within the larger debate over sensory attenuation: (1) there is an attenuation of prediction errors that depends upon the context in which sensory input is predicted (i.e., efference copy), and (2) sensory attenuation is a necessary consequence of self-generated movement irrespective of context (i.e., active inference). The results support the notion of active inference.     

Assessing miserly information processing: An expansion of the Cognitive Reflection Test

The Cognitive Reflection Test (CRT; Frederick, 2005) is designed to measure the tendency to override a prepotent response alternative that is incorrect and to engage in further reflection that leads to the correct response. It is a prime measure of the miserly information processing posited by most dual process theories. The original three-item test may be becoming known to potential participants, however. We examined a four-item version that could serve as a substitute for the original. Our data show that it displays a .58 correlation with the original version and that it has very similar relationships with cognitive ability, various thinking dispositions, and with several other rational thinking tasks. Combining the two versions into a seven-item test resulted in a measure of miserly processing with substantial reliability (.72). The seven-item version was a strong independent predictor of performance on rational thinking tasks after the variance accounted for by cognitive ability and thinking dispositions had been partialled out.     

When time is of the essence: The use of rational emotive behavior therapy (REBT) informed single-session therapy (SST) to alleviate social and golf-specific anxiety,and improve wellbeing and performance,in amateur golfers

Anxieties associated with the social evaluative nature of golf are present in the majority of athletes and impact directly on their wellbeing and objective performance. One potential intervention that could reduce social anxiety in golfers is rational emotive behavior therapy (REBT). There is limited research into the effectiveness of REBT in reducing social anxiety and even less research to assess if REBT can be delivered in time-constricted situations when the expectations for immediate results are high, as is the case with many handicap golfers. The current study used an idiographic single-case study design to assess the effects of REBT-informed single-session therapy (SST) on the social anxiety of five amateur golfers. REBT was employed in a short telephone call to target the performance issue, followed up with a single face-to-face session. Data were collected prior to, immediately following, and four weeks after the REBT intervention. Visual analysis following single-case guidelines revealed substantial reductions in irrational beliefs and social anxiety as well as improvements in wellbeing, scoring average, competition placings and handicap reductions in four out of five golfers. Discussion with golfers at a telephone follow-up indicated the positive receipt of REBT by the golfers and supported the visual analysis findings. This current study supports the effectiveness of REBT and also extends the research by demonstrating that REBT-informed SST can be an effective intervention, in a time-restricted environment, for those golfers with a clear target problem and who are ready to take care of business, providing clear implications for future research and practice.     

Inference and coherence in causal-based artifact categorization

In four experiments, we tested conditions under which artifact concepts support inference and coherence in causal categorization. In all four experiments, participants categorized scenarios in which we systematically varied information about artifacts’ associated design history, physical structure, user intention, user action and functional outcome, and where each property could be specified as intact, compromised or not observed. Consistently across experiments, when participants received complete information (i.e., when all properties were observed), they categorized based on individual properties and did not show evidence of using coherence to categorize. In contrast, when the state of some property was not observed, participants gave evidence of using available information to infer the state of the unobserved property, which increased the value of the available information for categorization. Our data offers answers to longstanding questions regarding artifact categorization, such as whether there are underlying causal models for artifacts, which properties are part of them, whether design history is an artifact’s causal essence, and whether physical appearance or functional outcome is the most central artifact property.     

Inference and the taking condition

It has recently been argued that inference essentially involves the thinker taking his premises to support his conclusion and drawing his conclusion because of this fact. However, this Taking Condition has also been criticized: If taking is interpreted as believing, it seems to lead to a vicious regress and to overintellectualize the act of inferring. In this paper, I examine and reject various attempts to salvage the Taking Condition, either by interpreting inferring as a kind of rule‐following, or by finding an innocuous role for the taking‐belief. Finally, I propose an alternative account of taking, according to which it is not a separate belief, but rather an aspect of the attitude of believing: Believing that p implies not only taking p to be true and taking oneself to believe that p, but also taking one's reasons q to support p, when the belief in question is held on account of an inference.