Stimulus-specific learning: disrupting the bow effect in absolute identification

The bow effect is ubiquitous in standard absolute identification experiments; stimuli at the center of the stimulus-set range elicit slower and less accurate responses than do others. This effect has motivated various theoretical accounts of performance, often involving the idea that end-of-range stimuli have privileged roles. Two other phenomena (practice effects and improved performance for frequently-presented stimuli) have an important but less explored consequence for the bow effect: Standard within-subjects manipulations of set size could disrupt the bow effect. We found this disruption for stimulus types that support practice effects (line length and tone frequency), suggesting that the bow effect is more fragile than has been thought. Our results also have implications for theoretical accounts of absolute identification, which currently do not include mechanisms for practice effects, and provide results consistent with those in the literature on stimulus-specific learning.     

Structure of the Wechsler Intelligence Scale for Children--Fourth Edition among a national sample of referred students

The structure of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV; D. Wechsler, 2003a) was analyzed via confirmatory factor analysis among a national sample of 355 students referred for psychoeducational evaluation by 93 school psychologists from 35 states. The structure of the WISC-IV core battery was best represented by four first-order factors as per D. Wechsler (2003b), plus a general intelligence factor in a direct hierarchical model. The general factor was the predominate source of variation among WISC-IV subtests, accounting for 48% of the total variance and 75% of the common variance. The largest 1st-order factor, Processing Speed, only accounted for 6.1% total and 9.5% common variance. Given these explanatory contributions, recommendations favoring interpretation of the 1st-order factor scores over the general intelligence score appear to be misguided.     

Probabilistic models of set-dependent and attribute-level best-worst choice

We characterize a class of probabilistic choice models where the choice probabilities depend on two scales, one with a value for each available option and the other with a value for the set of available options. Then, we develop similar results for a task in which a person is presented with a profile of attributes, each at a pre-specified level, and chooses the best or the best and the worst of those attribute-levels. The latter design is an important variant on previous designs using best-worst choice to elicit preference information, and there is various evidence that it yields reliable interpretable data. Nonetheless, the data from a single such task cannot yield separate measures of the “importance” of an attribute and the “utility” of an attribute-level. We discuss various empirical designs, involving more than one task of the above general type, that may allow such separation of importance and utility.     

An integrated model of choices and response times in absolute identification

Recent theoretical developments in the field of absolute identification have stressed differences between relative and absolute processes, that is, whether stimulus magnitudes are judged relative to a shorter term context provided by recently presented stimuli or a longer term context provided by the entire set of stimuli. The authors developed a model (SAMBA: selective attention, mapping, and ballistic accumulation) that integrates shorter and longer term memory processes and accounts for both the choices made and the associated response time distributions, including sequential effects in each. The model's predictions arise as a consequence of its architecture and require estimation of only a few parameters with values that are consistent across numerous data sets. The authors show that SAMBA provides a quantitative account of benchmark choice phenomena in classical absolute identification experiments and in contemporary data involving both choice and response time.     

Is absolute identification always relative? Comment on Stewart, Brown, and Chater (2005)

N. Stewart, G. D. A. Brown, and N. Chater's relative judgment model includes three core assumptions that enable it to predict accurately the vast majority of "classical" phenomena in absolute identification choices, but not the time taken to make them, including sequential effects, such as assimilation and contrast. These core assumptions, coupled with the parameter values used in the above-mentioned article, lead to the prediction that identification accuracy is low when a large stimulus on 1 trial is followed by a small stimulus on the next trial and vice versa. Data do not support this prediction. The authors identify a set of parameters that allow the model to better fit the data, but problems remain when the data are analyzed with a version of the discrimination measure (d') from signal detection theory. The fundamental problem is that the model fits data on average but at the expense of making incorrect predictions in detail.     

Random utility models with equality: An apparent,but not actual,generalization of random utility models

A probabilistic model for choice, and preference, is introduced that includes (Tversky's) elimination by aspects model, and the random utility model, as special cases. The model is based on a covert sequential elimination process, the element that is finally chosen in a simple choice experiment being the eventual lone survivor of the elimination process. The model leads us to question the usual form of simple choice experiments, in which a subject must (eventually) choose one of the currently available alternatives, and to suggest that a much more realistic experimental design would allow the subject the no-choice option, i.e., he may refuse to accept any of the currently available alternatives.     

A fixed rehearsal capacity interpretation of limits on absolute identification performance

The information transmitted in absolute identification quickly reaches its upper limit as the number of (one-dimensional) signals, and their range, is increased. Several explanations have been given of this phenomenon, but all are ad hoc in one way or another. Here we present a ‘memory’ or ‘rehearsal’ interpretation. The basic (psychological) representation of each signal in an absolute identification experiment is assumed to be quite accurate, and independent of the other stimuli used in the experiment. However, the identification of the stimulus presented on a particular trial is relative to a ‘frame’ (usually the range of stimuli in that experiment) that the subject must ‘rehearse’ using a fixed capacity rehearsal system. In special cases, this model reduces to earlier suggestions, but its general motivation seems somewhat less ad hoc than that of earlier ideas, and it is also easily applied to the absolute identification of multivariate signals and to magnitude estimation.     

Interobserver Agreement in Behavioral Research: Importance and Calculation

Behavioral researchers have developed a sophisticated methodology to evaluate behavioral change which is dependent upon accurate measurement of behavior. Direct observation of behavior has traditionally been the mainstay of behavioral measurement. Consequently, researchers must attend to the psychometric properties, such as interobserver agreement, of observational measures to ensure reliable and valid measurement. Of the many indices of interobserver agreement, percentage of agreement is the most popular. Its use persists despite repeated admonitions and empirical evidence indicating that it is not the most psychometrically sound statistic to determine interobserver agreement due to its inability to take chance into account. Cohen's (1960) kappa has long been proposed as the more psychometrically sound statistic for assessing interobserver agreement. Kappa is described and computational methods are presented.