A theory of attending, remembering, and reinforcement in delayed matching to sample

A theory of attending and reinforcement in conditional discriminations is extended to working memory in delayed matching to sample by adding terms for disruption of attending during the retention interval. Like its predecessor, the theory assumes that reinforcers and disruptors affect the independent probabilities of attending to sample and comparison stimuli in the same way as the rate of overt free-operant responding as suggested by Nevin and Grace, and that attending is translated into discriminative performance by the model of Davison and Nevin. The theory accounts for the effects of sample-stimulus discriminability and retention-interval disruption on the levels and slopes of forgetting functions, and for the diverse relations between accuracy and sensitivity to reinforcement reported in the literature. It also accounts for the effects of reinforcer probability in multiple schedules on the levels and resistance to change of forgetting functions; for the effects of reinforcer probabilities signaled within delayed-matching trials; and for the effects of reinforcer delay, sample duration, and intertrial-interval duration. The model accounts for some data that have been problematic for previous theories, and makes testably different predictions of the effects of reinforcer probabilities and disruptors on forgetting functions in multiple schedules and signaled trials.     

Invariance in Measurement and Prediction Revisited

Borsboom (Psychometrika, 71:425–440, 2006) noted that recent work on measurement invariance (MI) and predictive invariance (PI) has had little impact on the practice of measurement in psychology. To understand this contention, the definitions of MI and PI are reviewed, followed by results on the consistency between the two forms of invariance in the general case. The special parametric cases of factor analysis (strict factorial invariance) and linear regression analyses (strong regression invariance) are then described, along with findings on the inconsistency between the two forms of invariance in this context. Two numerical examples of inconsistency are reviewed in detail. The impact of violations of MI on accuracy of selection is illustrated. Finally, reasons for the slow dissemination of work on invariance are discussed, and the prospects for altering this situation are weighed. This paper is based on the Presidential Address given at the International Meeting of the Psychometric Society in Tokyo, Japan, on July 11, 2007. This research was supported by National Institute of Mental Health grants 1P30 MH 068685-01A1 and RO1 MH64707-01.     

人格判断的准确性研究述评

人格判断的准确性主要涉及到现实准确性、一致性和自我一他人一致性三个方面。现实准确性代表着人格判断和目标本来面目之间的一致性水平;一致性是指两个人或更多人对他人人格做出的判断之间的一致性水平;而自我一他人一致性则被认为是他人做出的判断和目标自我判断之间的一致性水平。人格判断的标准化问题是当前人格研究中的基本问题,也是人格研究的新动向之一。     

读者的元理解监测为什么不精确？

精确的元理解监测对随后的元理解控制和阅读理解有重要作用,但是,通常情况下,读者的元理解监测并不精确。回顾20余年的元理解监测研究,发现元理解监测的精确性主要受制于阅读材料特征、监测线索与标准测验特征等因素。未来研究应注意元理解监测的判断形式、监测线索及评价标准对元理解监测精确性的交互关联影响。     

Interpreting functional analysis outcomes using automated nonparametric statistical analysis

Current methods employed to interpret functional analysis data include visual analysis and post-hoc visual inspection (PHVI). However, these methods may be biased by dataset complexity, hand calculations, and rater experience. We examined whether an automated approach using nonparametric rank-based statistics could increase the accuracy and efficiency of functional analysis data interpretation. We applied Automated Nonparametric Statistical Analysis (ANSA) to a sample of 65 published functional analyses for which additional experimental evidence was available to verify behavior function. Results showed that exact behavior function agreement between ANSA and the publications authors was 83.1%, exact agreement between ANSA and PHVI was 75.4%, and exact agreement across all 3 methods was 64.6%. These preliminary findings suggest that ANSA has the potential to support the data interpretation process. A web application that incorporates the calculations and rules utilized by ANSA is accessible at https://ansa.shinyapps.io/ansa/     

Asking an eyewitness to predict their later lineup performance could harm the confidence–accuracy relationship

Few studies have investigated eyewitnesses' ability to predict their later lineup performance, known as predecision confidence. We applied calibration analysis in two experiments comparing predecision confidence (immediately after encoding but prior to a lineup) to postdecision confidence (immediately after a lineup) to determine which produces a superior relationship with lineup decision accuracy. Experiment 1 (N = 177) featured a multiple-block lineup recognition paradigm featuring several targets and lineups; Experiment 2 featured an eyewitness identification paradigm with a mock-crime video and a single lineup for each participant (N = 855). Across both experiments, postdecision confidence discriminated well between correct and incorrect lineup decisions, but predecision confidence was a poor predictor of accuracy. Moreover, simply asking for predecision confidence weakened the postdecision confidence–accuracy relationship. This implies that police should exercise caution when interviewing eyewitnesses, as they should not be asked to predict their ability to make an accurate lineup decision.     

Item Selection With Collaborative Filtering in On-The-Fly Multistage Adaptive Testing

An important design feature in the implementation of both computerized adaptive testing and multistage adaptive testing is the use of an appropriate method for item selection. The item selection method is expected to select the most optimal items depending on the examinees’ ability level while considering other design features (e.g., item exposure and item bank utilization). This study introduced collaborative filtering (CF) as a new method for item selection in the on-the-fly assembled multistage adaptive testing framework. The user-based CF (UBCF) and item-based CF (IBCF) methods were compared to the maximum Fisher information method based on the accuracy of ability estimation, item exposure rates, and item bank utilization under different test conditions (e.g., item bank size, test length, and the sparseness of training data). The simulation results indicated that the UBCF method outperformed the traditional item selection methods regarding measurement accuracy. Also, the IBCF method showed the most superior performance in terms of item bank utilization. Limitations of the current study and the directions for future research are discussed.     

Origins,uses of,and relations between goal programming and data envelopment analysis

Origins and uses of ‘goal programming’ and ‘data envelopment analysis’ (DEA) are identified and discussed. The purpose of this paper is not only to review some of the history of these developments, but also to show some of their uses (e.g. in statistical regression formulations) in order to suggest paths for possible further developments. Turning to how the two types of models relate to each other, the ‘additive model’ of DEA is shown to have the same structure as a goal programming model in which only ‘one‐sided deviations’ are permitted. A way for formally relating the two to each other is then provided. However, the objectives are differently oriented because goal programming is directed to future performances as part of the planning function whereas DEA is directed to evaluating past performances as part of the control function of management. Other possible ways of comparing and combining the two approaches are also noted including statistical regressions that utilize goal programming to ensure that the resulting estimates satisfy the multi‐criteria conditions that are often encountered in managerial applications. Both goal programming and DEA originated in actual applications that were successfully addressed. The research was then generalized and published. This leads to what is referred to as an ‘applications‐driven theory’ strategy for research that is also described in this paper. Copyright © 2006 John Wiley & Sons, Ltd.     

Towards statistical multicriteria decision modelling: a first approach

Many real life situations result from decisions taken by a very large number of decision makers. Among them, we may cite road traffic congestion, crowding during shopping, equity market behaviour, distribution of holiday destinations, etc. Furthermore, these decisions often depend on the optimisation of several conflicting criteria. In this paper, we introduce a new multicriteria tool based on Markov chains to model and manage these macroscopic phenomena. Finally, the road traffic congestion problem will be considered to illustrate the applicability of our approach. Copyright © 2003 John Wiley & Sons, Ltd.     

Inducing compensatory information processing through decision aids that facilitate effort reduction: an experimental assessment

This paper examines the role of computer‐based decision aids in reducing cognitive effort and therefore influencing strategy selection. It extends and complements the work reported in the behavioral decision theory literature on the role of effort and accuracy in choice tasks. The central proposition of the research is that if a decision aid makes a strategy that should lead to a more accurate outcome at least as easy to employ as a simpler, but less accurate, heuristic, then the use of a decision aid should induce that more accurate strategy and as a consequence improve decision quality. Otherwise, a decision aid may only influence decision‐making efficiency. This occurs because decision makers use a decision aid in such a way as to minimize their overall level of effort expenditure. Results from a laboratory experiment support this proposition. When a more accurate normative strategy is made less effortful to use, it is used. This result is consistent with the findings of our prior studies, but more clearly demonstrates that decision aids can induce the use of normatively oriented strategies. The key to inducing these strategies is to make the normative strategy easier to execute than competing alternative strategies. Copyright © 2000 John Wiley & Sons, Ltd.