Assessing the distinguishability of models and the informativeness of data

A difficulty in the development and testing of psychological models is that they are typically evaluated solely on their ability to fit experimental data, with little consideration given to their ability to fit other possible data patterns. By examining how well model A fits data generated by model B, and vice versa (a technique that we call landscaping), much safer inferences can be made about the meaning of a model's fit to data. We demonstrate the landscaping technique using four models of retention and 77 historical data sets, and show how the method can be used to: (1) evaluate the distinguishability of models, (2) evaluate the informativeness of data in distinguishing between models, and (3) suggest new ways to distinguish between models. The generality of the method is demonstrated in two other research areas (information integration and categorization), and its relationship to the important notion of model complexity is discussed.     

Influence of consonantal context on the pronunciation of vowels: a comparison of human readers and computational models

In two experiments, we found that college students' pronunciations of vowels in nonwords are influenced both by preceding and following consonants. The predominance of rimes in previous studies of reading does not appear to arise because readers are unable to pick up associations that cross the onset-rime boundary, but rather because English has relatively few such associations. Comparisons between people's vowel pronunciations and those produced by various computational models of reading showed that no model provided a good account of human performance on nonwords for which the vowel shows contextual conditioning. Possible directions for improved models are suggested.     

Remarks on the identifiability of thurstonian paired comparison models under multiple judgment

It is well-known that the representations of the Thurstonian models for difference judgment data are not unique. It has been shown that equivalence classes can be formed to provide a more meaningful partition of the covariance structures of the Thurstonian ranking models. In this paper, we examine the equivalence relations between Thurstonian covariance structure models for paired comparison data obtained under multiple judgment and discuss their implications on the general identification constraints and methods to check for parameter identifiability in restricted models.The author is indebted to Ulf Böckenholt and Albert Maydeu-Olivares for their significant comments and suggestions which led to considerable improvement in this article.     

Global and local covert visual attention: Evidence from a bayesian hidden markov model

Psychological, psychophysical and physiological research indicates that people switch between two covert attention states, local and global attention, while visually exploring complex scenes. The focus in the local attention state is on specific aspects and details of the scene, and on examining its content with greater visual detail. The focus in the global attention state is on exploring the informative and perceptually salient areas of the scene, and possibly on integrating the information contained therein. The existence of these two visual attention states, their relative prevalence and sequence in time has remained empirically untested to date. To fill this gap, we develop a psychometric model of visual covert attention that extends recent work on hidden Markov models, and we test it using eye-movement data. The model aims to describe the observed time series of saccades typically collected in eye-movement research by assuming a latent Markov process, indicative of the brain switching between global and local covert attention. We allow subjects to be in either state while exploring a stimulus visually, and to switch between them an arbitrary number of times. We relax the no-memory-property of the Markov chain. The model that we develop is estimated with MCMC methodology and calibrated on eye-movement data collected in a study of consumers' attention to print advertisements in magazines.We thank Dominique Claessens of Verify International for making the data available to us.     

What do computer models of cognition explain: a reply to Gobet

The differences between Gobet’s views and ours call attention to some points concerning the argumentative status of computational models. If we have two fundamentally different models which reasonably accurately simulate a phenomenon, we must ask, what is the argumentative status of the models in psychological terms. Moreover, if it is possible to present different models of same phenomena, what is the general argumentative power of models in psychology? As the kind of differences between our views and the ones of Gobet’s are common in modelling, we briefly call attention to these foundational issues in our paper.     

Psychoanalysis and Diplomacy: Part III. Potentials for and Obstacles Against Collaboration

Given the pervasive influence of Realpolitik over government and the study of international relations, and some inherent difficulties within the field of psychoanalysis, it is not surprising that political science and psychoanalysis remain distant cousins. Part III in this series on diplomacy and psychoanalysis discusses obstacles against collaboration between these two disciplines, but also points to areas where collaboration is possible and can be useful.     

A local model of concurrent performance

Concurrent procedures may be conceptualized as consisting of two pairs of schedules with only one pair operating at a time. One schedule of each pair arranges reinforcers for staying in the current alternative, and the other schedule arranges reinforcers for switching to the other alternative. These pairs alternate operation as the animal switches between choices. This analysis of the contingencies suggests that variables operating within an alternative produce behavior that conforms to the generalized matching law. Rats were exposed to one pair of stay and switch schedules in each condition, and the probabilities of reinforcement varied across conditions. Both run length and visit duration were power functions of the ratio of the probabilities of reinforcement for staying and switching. The local model, a model of performance on concurrent procedures, was derived from this power function. Performance on concurrent schedules was synthesized from the performances on the separate pairs. Both the generalized matching law and the local model fitted the synthesized concurrent performances. These results are consistent with the view that the contingencies in the alternative, the probability of stay and switch reinforcement, are responsible for performance consistent with the generalized matching law. These results are compatible with momentary maximizing and molar maximizing accounts of concurrent performance. Models of concurrent performance that posit comparisons among the alternatives are not easily applied to these results.     

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.     

The role of posttraumatic fear and social support in the relationship between trauma severity and posttraumatic growth among adolescent survivors of the Yaan earthquake

Middle school students in Lushan county (N = 315) were assessed 6 months after the Yaan earthquake using a trauma severity questionnaire, a posttraumatic fear questionnaire, a social support questionnaire and a posttraumatic growth inventory to examine the effects of posttraumatic fear and social support in the relationship between trauma severity and posttraumatic growth (PTG). The results showed that posttraumatic fear mediated the relationship between trauma severity and PTG, and social support moderated the relationship between posttraumatic fear and PTG. These findings suggested that trauma severity could be positively associated with PTG in a direct way or in an indirect way through posttraumatic fear. Moreover, posttraumatic fear had a positive relation to PTG under the condition of high social support level, whereas the relation was non‐significant when the level of social support was low. These results were discussed in terms of their implications for adolescents after trauma.