Do details bug you? Effects of perceptual richness in learning about biological change

People often have difficulty in understanding processes of biological change, and they typically reject drastic life cycle changes such as metamorphosis, except for animals with which they are familiar. Even after a lesson about metamorphosis, people often do not generalize to animals not seen during the lesson. This might be partially due to the perceptual richness of the diagrams typically used during lessons on metamorphosis, which serves to emphasize the individual animal rather than a class of animals. In two studies, we examined whether the perceptual richness of a diagram influences adults' learning and transfer of knowledge about metamorphosis. One study was conducted in a laboratory setting, and the other was online. In both studies, adults who saw the bland diagram during the lesson accurately transferred more than adults who saw the rich diagram during the lesson.     

A caveat on the Savage–Dickey density ratio: The case of computing Bayes factors for regression parameters

The Savage–Dickey density ratio is a simple method for computing the Bayes factor for an equality constraint on one or more parameters of a statistical model. In regression analysis, this includes the important scenario of testing whether one or more of the covariates have an effect on the dependent variable. However, the Savage–Dickey ratio only provides the correct Bayes factor if the prior distribution of the nuisance parameters under the nested model is identical to the conditional prior under the full model given the equality constraint. This condition is violated for multiple regression models with a Jeffreys–Zellner–Siow prior, which is often used as a default prior in psychology. Besides linear regression models, the limitation of the Savage–Dickey ratio is especially relevant when analytical solutions for the Bayes factor are not available. This is the case for generalized linear models, non-linear models, or cognitive process models with regression extensions. As a remedy, the correct Bayes factor can be computed using a generalized version of the Savage–Dickey density ratio.     

组织变革前非正式信息的作用机制

非正式信息是变革前信息沟通的重要组成部分, 对变革决策和执行有潜在的影响。围绕组织变革前非正式信息开展以下研究：(1)探究组织变革前非正式信息的内涵和结构; (2)基于心理因应和认知重构机制, 探索员工获取非正式信息之后, 其变革认知和情感的动态调整过程; (3)研究潜在的组织变革决策→非正式信息反馈→再决策过程, 即变革领导者通过获得员工变革认知和情感的反馈, 进行渐进决策优化的过程。研究结果能丰富变革沟通理论和指导我国变革实践。     

迪昂问题及其解决

迪昂问题是当代科学哲学争论的主题之一。波普尔、拉卡托斯和库恩都曾经对此问题给予不同的对待或解决。本文对此背景给以扼要的介绍,然后着重介绍和评价一种新的解决方案——基于贝叶斯方法的解决。相比之下,后一方案较为令人满意。     

创业警觉性、既有知识、创业经历对大学生创业机会识别的影响

采用“新手—创业经验丰富者” 对比范式,分别以114名在校无创业经历大学生和94名创业大学生作为被试,通过不同被试对自编复杂机会情景的反应搜集其对机会识别的表现,同时探讨了大学生创业警觉性、既有知识对创业机会识别的影响。结果表明：两类大学生创业警觉性、既有知识差异显著,创业大学生明显好于一般大学生。两类大学生在创业警觉性的三个维度以及既有知识的两个维度上均存在显著性差异,创业大学生均显著优于于一般大学生。创业大学生既有知识对机会识别具有显著影响;一般大学生创业警觉性对机会识别具有显著影响。此外,大学生既有知识可能通过警觉性影响机会识别。     

AN ANALYTIC FORM FOR THE INTERRESPONSE TIME ANALYSIS OF SHULL, GAYNOR, AND GRIMES WITH APPLICATIONS AND EXTENSIONS

Shull, Gaynor and Grimes advanced a model for interresponse time distribution using probabilistic cycling between a higher-rate and a lower-rate response process. Both response processes are assumed to be random in time with a constant rate. The cycling between the two processes is assumed to have a constant transition probability that is independent of bout length. This report develops an analytic form of the model which has a natural parametrization for a higher-rate within-bout responding and a lower-rate visit-initiation responding. The analytic form provides a convenient basis for both a nonlinear least-squares data reduction technique to estimate the model's parameters and Monte Carlo simulations of the model. In addition, the analytic formulation is extended to both a refractory period for the rats' behavior and, separately, the strongly-banded behavior seen with pigeons.     

"I've also experienced loss and fear": Effects of prior similar experience on empathy

Although it is frequently argued that empathy is increased by similar experiences, this idea has rarely been tested. This study investigated the relationship between empathy and prior similar experience. Participants read four different stories and rated the degree of empathy they felt. They also reported the extent to which they had prior similar experience of the events in the stories. We found that these self-reports of prior similar experience increased empathy for the persons in the stories. Similar experience may be an important situational antecedent for feeling empathy for another person. Pointing out similarities among experiences may be a fruitful means of training empathy.     

A Bayesian Nonparametric Approach to Test Equating

A Bayesian nonparametric model is introduced for score equating. It is applicable to all major equating designs, and has advantages over previous equating models. Unlike the previous models, the Bayesian model accounts for positive dependence between distributions of scores from two tests. The Bayesian model and the previous equating models are compared through the analysis of data sets famous in the equating literature. Also, the classical percentile-rank, linear, and mean equating models are each proven to be a special case of a Bayesian model under a highly-informative choice of prior distribution.