Estimating the polyserial correlation coefficient

We develop simple noniterative estimators of the polyserial correlation coefficient. A general relationship between the polyserial correlation and the point polyserial correlation is exploited to give extensions of Pearson's, Brogden's, and Lord's biserial estimators to the multicategory setting. The small sample and asmptotic properties of these estimators are studied in some detail. A comparison with maximum likelihood estimates shows that Lord's polyserial estimator is fairly efficient across three probability models.The authors would like to thank the referees for suggestions that improved the presentation of the paper.     

Delayed reinforcement of fixed-ratio performance without mediating exteroceptive conditioned reinforcement

The performance of pigeons was studied under conditions in which the completion of a fixed-ratio requirement was not contiguous with the presentation of a reinforcer. Timein and timeout periods alternated throughout the experimental sessions. Responses made by an experimental bird during the timein period were accumulated, and when a fixed-ratio requirement had been met, grain was presented to the experimental bird and a yoked control following their first response in the next timein period. Across most manipulations of the fixed-ratio requirement and of the duration of the timeout period, the response rates of the experimental birds were considerably higher than those of their controls, suggesting that the response-reinforcer dependency controlled the behavior of the experimental bird in the absence of a close temporal association between responding on the ratio schedule and reinforcer presentations.     

Problems with bootstrapping pearson correlations in very small bivariate samples

Efron'sMonte Carlo bootstrap algorithm is shown to cause degeneracies in Pearson'sr for sufficiently small samples. Two ways of preventing this problem when programming the bootstrap ofr are considered.     

On the optimality of the simultaneous redundancy transformations

The objective of this paper is to introduce and motivate additional properties and interpretations for the redundancy variables. It is shown that these variables can be derived by application of certain invariance arguments and without reference to the index of redundancy. In addition, an optimality property for the variables is presented which is important whenever one restricts attention in a study to a subset of the redundancy variables. This optimality property pertains to the subset rather than to the individual variables.This paper is based in part on the author's doctoral dissertation, Department of Statistics, Princeton, University. Research was conducted under the supervision of Lawrence S. Mayer.     

The polyserial correlation coefficient

The polyserial and point polyserial correlations are discussed as generalizations of the biserial and point biserial correlations. The relationship between the polyserial and point polyserial correlation is derived. The maximum likelihood estimator of the polyserial correlation is compared with a two-step estimator and with a computationally convenient ad hoc estimator. All three estimators perform reasonably well in a Monte Carlo simulation. Some practical applications of the polyserial correlation are described.By coincidence, the first author and the second and third authors learned that they were working independently on closely related problems and, consequently, decided to write a jointly authored paper.     

Canonical analysis of longitudinal and repeated measures data with stationary weights

When measuring the same variables on different occasions, two procedures for canonical analysis with stationary compositing weights are developed. The first, SUMCOV, maximizes the sum of the covariances of the canonical variates subject to norming constraints. The second, COLLIN, maximizes the largest root of the covariances of the canonical variates subject to norming constraints. A characterization theorem establishes a model building approach. Both methods are extended to allow for Cohort Sequential Designs. Finally a numerical illustration utilizing Nesselroade and Baltes data is presented.The authors wish to thank John Nesselroade for permitting us to use the data whose analysis we present.     

贝叶斯决策理论对复杂运动决策中运动预期的启发——以网球和足球为例

对运动决策的研究是认知运动心理学的一个重要领域。运动预期被认为是运动决策的核心, 受到运动学和非运动学信息的影响。其中, 对运动预期研究的一个关键问题是探讨不同信息源对运动结果预期的贡献以及两者之间的相互作用。研究者运用贝叶斯决策理论解释运动预期中不同信息的整合过程, 分析运动员在复杂的竞赛情景中如何做出最佳决策, 尤其是对该理论在网球和足球领域的潜在应用进行分析。在不确定的情况下, 竞技体育中并非所有的选择、结果或概率都是已知的, 故有研究者认为概率论和经典的决策理论不能有效解决此类问题。然而新近提出的启发式近似, 为运动员在贝叶斯框架下如何快速做出选择提供了理论依据：首先, 在复杂和有时间压力的竞赛情景中, 启发式近似假设运动员依据竞赛中不同信息源的不确定程度, 很可能选择在运动学信息和情境先验之间进行切换启发式, 提高运动预期的效率。其次, 判断效用通过卷积效应影响两种信息源的整合, 降低情境先验的影响程度。     

教与学的大脑：人际神经科学助推教育研究

如何从神经生理层面刻画教育活动的人际互动模式和动态性是教育神经科学面临的一个重要挑战。人际神经科学视角为其提供了可能的解决途径; 这一新兴的视角通过记录和分析进行同一认知活动时两人或多人大脑活动之间的关联, 来揭示大脑活动的群体模式。目前, 人际神经科学方法已被应用于教育研究, 例如监控教学过程、预测教学效果和识别教学影响因素, 相应的研究成果对教育活动具有重要启示。未来的研究者可以更多地关注不同学习水平的学生大脑的互动机制及人际神经科学方法应用于技能教学及线上教学评估的巨大潜力。     

Shared lesion correlates of semantic and letter fluency in post-stroke aphasia

Lesion–symptom mapping studies have reported a temporal versus frontal dissociation between semantic and letter fluency, and mixed evidence regarding the role of white matter. Mass-univariate and multivariate lesion–symptom mapping was used to identify regions associated with semantic and letter fluency deficits in post-stroke aphasia. Multivariate LSM revealed broad networks including underlying white matter, and substantial overlap between both types of fluency, suggesting that semantic fluency and letter fluency largely rely on the same neural system. All data are available on OSF.     

Blind justice: Fairness to groups and the do-no-harm principle

People are reluctant to harm some people in order to help others, even when the harm is less than the forgone help (the harm resulting from not acting). The present studies use hypothetical scenarios to argue that these judgments go against what the subjects themselves would take to be the best overall outcome. When the outcomes in question are income gains and losses for two groups of farmers, subjects judge the harm they would not impose through their action to be smaller than the harm they would impose through inaction. Some subjects refuse to reduce cure rates for one group of AIDS patients in order to increase cure rates more for another group, even when group membership was unknowable to anyone, so that, from each patient's point of view, the change would increase the probability of cure. Likewise, they resisted a vaccine that reduced overall mortality in one group but increased deaths from side effects in another group, even when, again, group membership was unknowable. Some people apply a do-no-harm principle to groups without apparent understanding of how such a principle might be justified in terms of its consequences. The capacity for such judgments makes them vulnerable to learning principles that have no justification at all.