A test of the diffusion model explanation for the worst performance rule using preregistration and blinding

People with higher IQ scores also tend to perform better on elementary cognitive-perceptual tasks, such as deciding quickly whether an arrow points to the left or the right Jensen (2006). The worst performance rule (WPR) finesses this relation by stating that the association between IQ and elementary-task performance is most pronounced when this performance is summarized by people’s slowest responses. Previous research has shown that the WPR can be accounted for in the Ratcliff diffusion model by assuming that the same ability parameter—drift rate—mediates performance in both elementary tasks and higher-level cognitive tasks. Here we aim to test four qualitative predictions concerning the WPR and its diffusion model explanation in terms of drift rate. In the first stage, the diffusion model was fit to data from 916 participants completing a perceptual two-choice task; crucially, the fitting happened after randomly shuffling the key variable, i.e., each participant’s score on a working memory capacity test. In the second stage, after all modeling decisions were made, the key variable was unshuffled and the adequacy of the predictions was evaluated by means of confirmatory Bayesian hypothesis tests. By temporarily withholding the mapping of the key predictor, we retain flexibility for proper modeling of the data (e.g., outlier exclusion) while preventing biases from unduly influencing the results. Our results provide evidence against the WPR and suggest that it may be less robust and less ubiquitous than is commonly believed.     

Individual differences,aging, and IQ in two-choice tasks

The effects of aging and IQ on performance were examined in three two-choice tasks: numerosity discrimination, recognition memory, and lexical decision. The experimental data, accuracy, correct and error response times, and response time distributions, were well explained by Ratcliff’s (1978) diffusion model. The components of processing identified by the model were compared across levels of IQ (ranging from 83 to 146) and age (college students, 60–74, and 75–90 year olds). Declines in performance with age were not significantly different for low compared to high IQ subjects. IQ but not age had large effects on the quality of the evidence that was obtained from a stimulus or memory, that is, the evidence upon which decisions were based. Applying the model to individual subjects, the components of processing identified by the model for individuals correlated across tasks. In addition, the model’s predictions and the data were examined for the “worst performance rule”, the finding that age and IQ have larger effects on slower responses than faster responses.     

A model for evidence accumulation in the lexical decision task

We present a new model for lexical decision, REM-LD, that is based on REM theory (e.g., ). REM-LD uses a principled (i.e., Bayes' rule) decision process that simultaneously considers the diagnosticity of the evidence for the 'WORD' response and the 'NONWORD' response. The model calculates the odds ratio that the presented stimulus is a word or a nonword by averaging likelihood ratios for lexical entries from a small neighborhood of similar words. We report two experiments that used a signal-to-respond paradigm to obtain information about the time course of lexical processing. Experiment 1 verified the prediction of the model that the frequency of the word stimuli affects performance for nonword stimuli. Experiment 2 was done to study the effects of nonword lexicality, word frequency, and repetition priming and to demonstrate how REM-LD can account for the observed results. We discuss how REM-LD could be extended to account for effects of phonology such as the pseudohomophone effect, and how REM-LD can predict response times in the traditional 'respond-when-ready' paradigm.     

Morningness-eveningness correlates with verbal ability in women but not men

Individuals differ along a continuum of preference for diurnal activity level, known as Morningness-Eveningness. Some evidence suggests that an Eveningness orientation (i.e., preference for later rise and bed times) is weakly associated with higher cognitive ability, but no studies have examined this relationship using clinically accepted, psychometrically valid measures of cognitive ability. The present study examined the correlation between Morningness-Eveningness with scores on the Wechsler Abbreviated Scale of Intelligence (WASI) of 54 healthy volunteers. Lower Morningness (i.e., Greater Eveningness) orientation was correlated (r = -.23) with higher Verbal IQ for the entire sample. When the data were examined separately by sex, the correlation between Morningness-Eveningness and Verbal IQ was significant for women (r = -.44) but not for men (r = -.09).     

Discretionary task interleaving: heuristics for time allocation in cognitive foraging

When participants allocated time across 2 tasks (in which they generated as many words as possible from a fixed set of letters), they made frequent switches. This allowed them to allocate more time to the more productive task (i.e., the set of letters from which more words could be generated) even though times between the last word and the switch decision ("giving-up times") were higher in the less productive task. These findings were reliable across 2 experiments using Scrabble tasks and 1 experiment using word-search puzzles. Switch decisions appeared relatively unaffected by the ease of the competing task or by explicit information about tasks' potential gain. The authors propose that switch decisions reflected a dual orientation to the experimental tasks. First, there was a sensitivity to continuous rate of return--an information-foraging orientation that produced a tendency to switch in keeping with R. F. Green's (1984) rule and a tendency to stay longer in more rewarding tasks. Second, there was a tendency to switch tasks after subgoal completion. A model combining these tendencies predicted all the reliable effects in the experimental data.     

The Role of Tentativeness in Perceiving Architecture and Art: A Far-from-Equilibrium Ecological Perspective

Two experiments examined performance in collision avoidance situations. In both experiments participants were asked to initiate a discrete maneuver to avoid a collision at the last possible moment. The affordances of the situations were varied as a function of vehicle dynamics and the functional consequences associated with responding too late or too early. The results were examined in the context of a 2-dimensional functional state space with dimensions associated with optical angle and optical expansion rate. The patterns of performance showed that the actions were consistent with decision rules that could be specified in terms of linear functions of the two optical variables. In most cases, performance at early stages of learning suggested that people were using an Expansion Rate Criterion. With practice, people would tune to a decision rule that was appropriate for the specific vehicle dynamics tested. The results are discussed in relation to the role of three factors in shaping ultimate performance: (a) tasks constraints (i.e., affordances), (b) information constraints (i.e., optical structure), and (c) experience (i.e., learning).     

An integrated perspective on the relation between response speed and intelligence

Research in the field of mental chronometry and individual differences has revealed several robust regularities (Jensen, 2006). These include right-skewed response time (RT) distributions, the worst performance rule, correlations with general intelligence (g) that are more pronounced for RT standard deviations (RTSD) than they are for RT means (RTm), an almost perfect linear relation between individual differences in RTSD and RTm, linear Brinley plots, and stronger correlations between g and inspection time (IT) than between g and RTm. Here we show how all these regularities are manifestations of a single underlying relationship, when viewed through the lens of Ratcliff’s diffusion model ( [Ratcliff, 1978] and [Ratcliff et al., 2008] ). The single underlying relationship is between individual differences in general intelligence and individual differences in “drift rate”, which is just the speed of information processing in Ratcliff’s model. We also test and confirm a strong prediction of the diffusion model, namely that the worst performance rule generalizes to phenomena outside of the field of intelligence. Our approach provides an integrative perspective on intelligence findings.     

Dutch plural inflection: the exception that proves the analogy

We develop the view that inflection is driven partly by non-phonological analogy and that non-phonological information is of particular importance to the inflection of non-canonical roots, which in the view of [Marcus, G. F., Brinkmann, U., Clahsen, H., Wiese, R., & Pinker, S. (1995). German inflection: the exception that proves the rule. Cognitive Psychology, 29, 189-256.] are inflected by a symbolic rule process. We used the Dutch plural to evaluate these claims. An analysis of corpus data shows that a model using non-phonological information (orthography) produces significantly fewer errors on plurals of non-canonical Dutch nouns, in particular borrowings, than a model that includes only phonological information. Moreover, we show that a double default system, as proposed by Pinker [Pinker, S. (1999). Words and rules. London: Phoenix.], does not offer an advantage over the latter model. A second study, examining the use of orthography in an online plural production task, shows that, in Dutch, the chosen pseudoword plural is significantly affected by non-phonological information. A final simulation study confirms that these results are in line with a model of inflectional morphology that explains the inflection of non-canonical roots by non-phonological analogy instead of by a default rule process.     

Eliciting Consumer Choice Heuristics: Sales Representives' Persuasion Strategies

Research has shown that consumers spend little cognitive effort in marketplace decisions (i.e., information acquisition, evaluation of alternatives). In fact, consumers simplify decision making by using decision rules learned from previous purchases. The present research explores the notion that during the course of a sales interaction, sales representatives may use expressions (i.e., primes) that encourage consumers to invoke previously used decision rules. These decision rules lead consumers to consider factors not necessarily relevant to the purchase decision (e.g., what others will think, reciprocate sales representatives' efforts, missed opportunities). Thus, consumers' thoughts are diverted from more pertinent factors such as budget and timing of the purchase. Moreover, consumers persuade themselves to purchase via thoughts concerning the decision rule and visual imagery associated with consumption. The notions of priming and schema- directed thinking are used to explain how sales representatives elicit consumers' decision rules from long-term memory. Implications of these techniques are made with regards to relationship management.     

A revision of the psychological refractory period

A brief review of the major psychological refractory period (PRP) theories reveals that they have lost their original objective, i.e., to explain human information processing under rapid sequential stimulation. Conventional data interpretation has restricted attention to delay of reaction times as a result of interstimulus interval (ISI) variation. This form of data interpretation fails to capture important performance aspects under double-stimulation, e.g., the phenomenon that stimulus complexity affects the processing rate. Effects of stimulus rate and complexity are better analyzed in terms of reaction times as well as interresponse intervals (IRI). If this is done, behavioral phenomena emerge that cannot be explained within the frame of any of the existing PRP theories. To account for these newly revealed phenomena a processing interrupt model is introduced which is based on three major hypotheses: single-channel processor, additive stages, and perceptual interrupt facility.     

A systematic literature review of the average IQ of sub-Saharan Africans

On the basis of several reviews of the literature, Lynn [Lynn, R., (2006). Race differences in intelligence: An evolutionary analysis. Augusta, GA: Washington Summit Publishers.] and Lynn and Vanhanen [Lynn, R., & Vanhanen, T., (2006). IQ and global inequality. Augusta, GA: Washington Summit Publishers.] concluded that the average IQ of the Black population of sub-Saharan Africa lies below 70. In this paper, the authors systematically review published empirical data on the performance of Africans on the following IQ tests: Draw-A-Man (DAM) test, Kaufman-Assessment Battery for Children (K-ABC), the Wechsler scales (WAIS & WISC), and several other IQ tests (but not the Raven's tests). Inclusion and exclusion criteria are explicitly discussed. Results show that average IQ of Africans on these tests is approximately 82 when compared to UK norms. We provide estimates of the average IQ per country and estimates on the basis of alternative inclusion criteria. Our estimate of average IQ converges with the finding that national IQs of sub-Saharan African countries as predicted from several international studies of student achievement are around 82. It is suggested that this estimate should be considered in light of the Flynn Effect. It is concluded that more psychometric studies are needed to address the issue of measurement bias of western IQ tests for Africans.     

Bayesian parameter estimation in the Expectancy Valence model of the Iowa gambling task

The purpose of the popular Iowa gambling task is to study decision making deficits in clinical populations by mimicking real-life decision making in an experimental context. Busemeyer and Stout [Busemeyer, J. R., & Stout, J. C. (2002). A contribution of cognitive decision models to clinical assessment: Decomposing performance on the Bechara gambling task. Psychological Assessment, 14, 253-262] proposed an “Expectancy Valence” reinforcement learning model that estimates three latent components which are assumed to jointly determine choice behavior in the Iowa gambling task: weighing of wins versus losses, memory for past payoffs, and response consistency. In this article we explore the statistical properties of the Expectancy Valence model. We first demonstrate the difficulty of applying the model on the level of a single participant, we then propose and implement a Bayesian hierarchical estimation procedure to coherently combine information from different participants, and we finally apply the Bayesian estimation procedure to data from an experiment designed to provide a test of specific influence.     

Bootstrap-Calibrated Interval Estimates for Latent Variable Scores in Item Response Theory

In most item response theory applications, model parameters need to be first calibrated from sample data. Latent variable (LV) scores calculated using estimated parameters are thus subject to sampling error inherited from the calibration stage. In this article, we propose a resampling-based method, namely bootstrap calibration (BC), to reduce the impact of the carryover sampling error on the interval estimates of LV scores. BC modifies the quantile of the plug-in posterior, i.e., the posterior distribution of the LV evaluated at the estimated model parameters, to better match the corresponding quantile of the true posterior, i.e., the posterior distribution evaluated at the true model parameters, over repeated sampling of calibration data. Furthermore, to achieve better coverage of the fixed true LV score, we explore the use of BC in conjunction with Jeffreys’ prior. We investigate the finite-sample performance of BC via Monte Carlo simulations and apply it to two empirical data examples.     

A Dynamic Model for Rule Induction Tasks

In this paper, a model for performance on rule induction tasks (e.g., items on intelligence tests) is developed. The model simultaneously specifies distributions for response times and response accuracies on an item-by-item basis. It is dynamic in the sense that it can be used to specify and test different ways of learning throughout a test. Three versions of the general model (i.e., with three different learning rules) are described and the fit of these versions is investigated in two datasets on solving number series. The results indicate that one of these versions (one of the learning rules) is better at accounting for the data.     

A computational model of the Simon effect

Even though stimulus location is task irrelevant, reaction times are faster when the location of the stimulus corresponds with the location of the response than when it does not. This phenomenon is called the Simon effect. Most accounts of the Simon effect are based on the assumption that it arises from a conflict between the spatial code of the stimulus and that of the response. In this paper a computational model of this hypothesis is presented. It provides a computationally explicit mechanism of the Simon effect. Consistent with human performance, the model provides reaction times that indicate both an advantage for the ipsilateral, corresponding response (i.e., facilitation) and a disadvantage of the contralateral, noncorresponding response (i.e., inhibition). In addition, the model accounts for the fact that the size for the effect depends on task difficulty.     

部件的语音信息对于中文假字和非字判断的影响

通过两个实验探索部件的语音信息在人造汉字判断过程中的作用。实验一通过操纵部件的独立性和部件位置的合法性分别探讨部件语音信息和位置信息对于人造字判断的影响。结果发现,与部件不独立的假字相比,判断部件独立的假字需要更长的时间,正确率也更低;但是部件的独立性并不影响对非字的判断。实验二通过控制部件本身是否发音和部件是否能做真字的声旁这两个因素,发现上述两个语音因素均影响假字的判断：和部件本身不能发音的假字相比,判断部件本身能发音的假字反应时更长,正确率更低;和部件不能做声旁的假字相比,判断部件能做声旁的假字反应时更长,正确率更低。结果还发现部件所包含的语音信息越多,假字判断的正确率就越低。在最后的讨论部分,根据实验结果构建了一个关于识别人造字和低频字的认知加工模型。     

Learning in noise: Dynamic decision-making in a variable environment

In engineering systems, noise is a curse, obscuring important signals and increasing the uncertainty associated with measurement. However, the negative effects of noise are not universal. In this paper, we examine how people learn sequential control strategies given different sources and amounts of feedback variability. In particular, we consider people’s behavior in a task where short- and long-term rewards are placed in conflict (i.e., the best option in the short-term is worst in the long-term). Consistent with a model based on reinforcement learning principles [Gureckis, T., & Love, B.C. Short term gains, long term pains: How cues about state aid learning in dynamic environments. Cognition (in press)], we find that learners differentially weight information predictive of the current task state. In particular, when cues that signal state are noisy, we find that participants’ ability to identify an optimal strategy is strongly impaired relative to equivalent amounts of noise that obscure the rewards/valuations of those states. In other situations, we find that noise and noise in reward signals may paradoxically improve performance by encouraging exploration. Our results demonstrate how experimentally-manipulated task variability can be used to test predictions about the mechanisms that learners engage in dynamic decision making tasks.     

Effects of changing compatibility relationships on reaction time to the first stimulus in a double-stimulation task

This study investigated the effects of manipulating the response requirement to the second stimulus (S2) on reaction time (RT) to the first stimulus (S1) in a double-stimulation choice RT task. Forty subjects responded to the 100 msec presentation of a left or right light by pressing the key on the same or opposite side as the light. Treatment conditions included a single-stimulation control (no S2 presented), and two double-stimulation conditions each requiring two responses (R1 and R2) in close succession, in one of these latter conditions, the rule governing R2 was the same as that governing R1 while, in the other, the rule governing R2 changed. Results showed the typical double-stimulation effect; i.e., increased latency of R1 when it was followed by S2 - R2. More importantly, R1 latency was increased further when the rules governing R1 and R2 were different. Results are discussed in terms of divided preparation capacity as well as other theories of the psychological refractory period.     

Explaining use of information in public policymaking

In recent years, scholars have attempted to understand the role of information in policymaking by developing several models of information utilization and have tested them empirically, at both national and state levels. This paper has called into question past studies as they relate to describing and explaining use of information. This paper tests an integrated model of information utilization that contains four sets of primary variables: decision makers’ environments (i.e., nature of policy issues), organization, individual characteristics, and characteristics of information. Based on the conceptual framework, a path model is built and tested against data about knowledge utilization and policy change in two areas of mental health policy (i.e., service and financing). The findings of the study have demonstrated that decision makers’ behavior does not conform to the assumptions put forward by either the organizational interest (e.g., information source or content of information) or the communications perspective (e.g., decision makers’ attitudes toward social science research). Instead, we have shown that information utilization is affected directly and indirectly by a variety of factors and their linkage, and not dominated by one set of factors that is defined by a singe perspective. The most important paths in the model are those between factors associated with information (e.g., the amount of information received or information source) and the use of information. Interestingly, these factors also play the role of major intervening mechanisms for linking other factors to decision makers’ use of information. More importantly, the general pattern of the findings indicates that policy areas make a difference in the process of information utilization.     

Subjective reports of stimulus,response, and decision times in speeded tasks: How accurate are decision time reports?

Four experiments examined how accurately participants can report the times of their own decisions. Within an auditory reaction time (RT) task, participants reported the time at which (a) the tone was presented, (b) they decided on the response, or (c) the response key was pressed. Decision time reports were checked for plausibility against the actual RTs, and we compared the effects of experimental manipulations on these two measures to see whether the reported decision times showed appropriate effects. In addition, we estimated the amount of error associated with individual decision time reports by checking how often participants’ decision time reports were implausibly early (i.e., before stimulus onset) or late (i.e., after response), and by using several quantitative models. Overall, the results suggest that decision time reports are not very accurate but they may be usable for some purposes.