Integrating Covariates into Social Relations Models: A Plausible Values Approach for Handling Measurement Error in Perceiver and Target Effects

The Social Relations Model (SRM) is a conceptual and analytical approach to examining dyadic behaviors and interpersonal perceptions within groups. In an SRM, the perceiver effect describes a person's tendency to perceive other group members in a certain way, whereas the target effect measures the tendency to be perceived by others in certain ways. In SRM research, it is often of interest to relate these individual SRM effects to covariates. However, the estimated individual SRM effects might not provide a very reliable measure of the true, unobserved SRM effects, resulting in distorted estimates of associations with other variables. This article introduces a plausible values approach that allows users to correct for measurement error when assessing the association of individual SRM effects with other individual difference variables. In the plausible values approach, the latent, true individual SRM effects are treated as missing values and are imputed from an imputation model by applying Bayesian estimation techniques. In a simulation study, the statistical properties of the plausible values approach are compared with two approaches that have been used in previous research. A data example from educational psychology is presented to illustrate how the plausible values approach can be implemented with the software WinBUGS.     

建构反应题中能力估计准确性的影响因素:评分者人数和项目个数的交互作用

采用康春花、孙小坚和曾平飞(2016)提出的等级反应多水平侧面模型探讨了评分者人数和项目个数对被试能力估计准确性的影响。模拟研究的结果表明:(1)随着项目个数的增加,估计值与真值之间的相关也不断增加;(2)评分者人数和项目个数在平均绝对偏差(MAB)和误差均方根(RMSE)上的主效应均显著,两者间的交互效应也显著;(3)简单效应分析发现,当项目较少时,3个评分者条件下的能力估计准确性最好; 随着项目个数的增加,4个评分者的估计误差迅速下降,且表现变为最好。     

Links between self-reported and laboratory behavioral impulsivity

Havik, M., Jakobson, A., Tamm, M., Paaver, M., Konstabel, K., Uusberg, A., Allik, J., Ööpik, V. & Kreegipuu, K. (2012). Links between self‐reported and laboratory behavioral impulsivity. Scandinavian Journal of Psychology 53, 216–223. A major problem in the research considering impulsivity is the lack of mutual understanding on how to measure and define impulsivity. Our study examined the relationship between self‐reported impulsivity, behavioral excitatory and inhibitory processes and time perception. Impulsivity – fast, premature, thoughtless or disinhibited behavior – was assessed in 58 normal, healthy participants (30 men, mean age 21.9 years). Self‐reported impulsivity as measured by Adaptive and Maladaptive Impulsivity Scale (AMIS) and behavioral excitatory and inhibitory processes as measured by Stop Signal Task were not directly related. Time perception, measured by the retrospective Time Estimation Task, was related to both. The length of the perceived time interval was positively correlated to AMIS Disinhibition subscale and negatively to several Stop Signal Task parameters. The longer subjects perceived the duration to last, the higher was their score on Disinhibition scale and the faster were their reactive responses in the Stop Signal Task. In summary our findings support the idea of cognitive tempo as a possible mechanism underlying impulsive behavior.     

Test theory without an answer key

A general model is presented for homogeneous, dichotomous items when the answer key is not known a priori. The model is structurally related to the two-class latent structure model with the roles of respondents and items interchanged. For very small sets of respondents, iterative maximum likelihood estimates of the parameters can be obtained by existing methods. For other situations, new estimation methods are developed and assessed with Monte Carlo data. The answer key can be accurately reconstructed with relatively small sets of respondents. The model is useful when a researcher wants to study objectively the knowledge possessed by members of a culturally coherent group that the researcher is not a member of.This research was supported by NSF Grant No. SES-8320173 to the authors. We gratefully acknowledge comments and suggestions from John Boyd, Tarow Indow, and Kathy Maher as well as the editor and several anonymous referees.     

情绪体验影响估算策略运用的认知与脑机制

揭示情绪体验影响个体完成各种认知任务的认知神经机制是研究者关注的热点问题。以往研究主要采用问卷法和行为实验, 集中考察了焦虑对估算策略运用的影响, 但这种影响潜在的脑机制尚不清楚, 对焦虑以外的情绪体验与估算策略运用之间关系的研究也极其缺乏, 而情绪调节对估算策略运用影响方面的研究基本处于空白。本研究将采用面孔表情图片作为情绪刺激材料, 结合事件相关电位(event related potential, ERP)技术, 采用启动范式, 尝试从外显和内隐两个角度, 考察不同效价的情绪体验在估算策略运用过程中所起的作用, 进而揭示情绪调节影响估算策略执行的时间动态特征和大脑激活模式。这将有助于充分认识情绪体验影响估算策略运用的认知与脑机制, 为更好的优化估算策略运用效果提供实证依据。     

Translating Toulmin Diagrams: Theory Neutrality in Argument Representation

The Toulmin diagram layout is very familiar and widely used, particularly in the teaching of critical thinking skills. The conventional box-and-arrow diagram is equally familiar and widespread. Translation between the two throws up a number of interesting challenges. Some of these challenges (such as the relationship between Toulmin warrants and their counterparts in traditional diagrams) represent slightly different ways of looking at old and deep theoretical questions. Others (such as how to allow Toulmin diagrams to be recursive) are diagrammatic versions of questions that have already been addressed in artificial intelligence models of argument. But there are further questions (such as the relationships between refutations, rebuttals and undercutters, and the roles of multiple warrants) that are posed as a specific result of examining the diagram inter-translation problem. These three classes of problems are discussed. To the first class are addressed solutions based on engineering pragmatism; to the second class, are addressed solutions drawn from the appropriate literature; and to the third class, fuller exploration is offered justifying the approaches taken in developing solutions that offer both pragmatic utility and theoretical interest. Finally, these solutions are explored briefly in the context of the Araucaria system, showing the ways in which analysts can tackle arguments either using one diagrammatic style or another, or even a combination of the two.     

Multilevel Reliability Measures of Latent Scores Within an Item Response Theory Framework

Abstract

This paper evaluated multilevel reliability measures in two-level nested designs (e.g., students nested within teachers) within an item response theory framework. A simulation study was implemented to investigate the behavior of the multilevel reliability measures and the uncertainty associated with the measures in various multilevel designs regarding the number of clusters, cluster sizes, and intraclass correlations (ICCs), and in different test lengths, for two parameterizations of multilevel item response models with separate item discriminations or the same item discrimination over levels. Marginal maximum likelihood estimation (MMLE)-multiple imputation and Bayesian analysis were employed to evaluate the accuracy of the multilevel reliability measures and the empirical coverage rates of Monte Carlo (MC) confidence or credible intervals. Considering the accuracy of the multilevel reliability measures and the empirical coverage rate of the intervals, the results lead us to generally recommend MMLE-multiple imputation. In the model with separate item discriminations over levels, marginally acceptable accuracy of the multilevel reliability measures and empirical coverage rate of the MC confidence intervals were found in a limited condition, 200 clusters, 30 cluster size, .2 ICC, and 40 items, in MMLE-multiple imputation. In the model with the same item discrimination over levels, the accuracy of the multilevel reliability measures and the empirical coverage rate of the MC confidence intervals were acceptable in all multilevel designs we considered with 40 items under MMLE-multiple imputation. We discuss these findings and provide guidelines for reporting multilevel reliability measures.     

The effect of food toppings on calorie estimation and consumption

In this research we examine the effect of adding a food topping to the base food on consumers' calorie estimation and consumption of the augmented food (base food plus topping). We show that consumers underestimate the calorie content of augmented food with an unhealthy base, especially when the topping is healthy. However, consumers are less likely to underestimate the calorie content of augmented food with a healthy base, regardless of whether the topping is healthy or unhealthy. Further, we show that adding a healthy topping to an unhealthy base makes consumers not only underestimate the calorie content but also eat more of the augmented food.