Analysis of a two-alternative force-choice signal detection theory model

A basic problem in psychophysics is recovering the mean internal response and noise amplitude from sensory discrimination data. Since these components cannot be estimated independently, several indirect methods were suggested to resolve this issue. Here we analyze the two-alternative force-choice method (2AFC), using a signal detection theory approach, and show analytically that the 2AFC data are not always suitable for a reliable estimation of the mean internal responses and noise amplitudes. Specifically, we show that there is a subspace of internal parameters that are highly sensitive to sampling errors (singularities), which results in a large range of estimated parameters with a finite number of experimental trials. Four types of singular models were identified, including the models where the noise amplitude is independent of the stimulus intensity, a situation often encountered in visual contrast discrimination. Finally, we consider two ways to avoid singularities: (1) inserting external noise to the stimuli, and (2) using one-interval forced-choice scaling methods (such as the Thurstonian scaling method for successive intervals).     

Mapping the Structure of Human Values through Conceptual Representations

The present research provides the first direct examination of human values through concept categorization tasks that entail judging the meaning of values. Seven studies containing data from nine samples (N = 1086) in two countries (the UK and Brazil) asked participants to compare the meaning of different values found within influential quasi‐circumplex model of values. Different methods were used across experiments, including direct similarity judgment tasks, pile sorting, and spatial arrangement. The results of these diverse conceptual assessments corresponded to spatial configurations that are broadly convergent with Schwartz's model, both between and within participants. © 2018 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology     

计算机化多维测验中作答时间和作答精度数据的联合分析

随着心理与教育测量研究的发展和科技的进步,计算机化(大规模)测验逐渐受到人们的关注。为探究在计算机化多维测验中如何利用作答时间数据来辅助评估多维潜在能力,以及为我国义务教育阶段教育质量监测提供数据分析方法上的理论支持。本研究以2012年和2015年国际学生能力评估(PISA)计算机化数学测验数据为例,提出了一种可同时利用作答时间和作答精度数据的联合作答与时间的多维Rasch模型。根据新模型对PISA数据的分析结果,表明引入作答时间数据,不仅有助于提高模型参数的估计精度,还有助于数据分析者利用被试的作答时间信息来做进一步的决策和干预(e.g., 对异常作答行为或预备知识的诊断)。     

双因子模型MCAT中多级评分项目选题策略的比较

双因子模型假设测验考察一个一般因子和多个组因子,符合很多教育和心理测验的因素结构。“维度缩减”方法将参数估计中多维积分计算化简为多个迭代二维积分,是双因子模型的重要特征。本文针对考察多级评分项目的计算机化自适应测验,首先推导双因子等级反应模型下Fisher信息量的计算,然后推导“维度缩减”方法在项目选择方法中的应用,最后在低、中、高双因子模式题库中比较D-优化方法、后验加权Fisher信息D优化方法(PDO)、后验加权Kullback-Leibler方法(PKL)、连续熵(CEM)和互信息(MI)方法在能力估计的相关、均方根误差、绝对值偏差和欧氏距离的表现。模拟研究表明：(1)双因子模式越强,即一般因子和组因子在项目上的区分度的差异越小,一般因子估计精度降低,组因子估计精度增加,整体能力的估计精度提高;(2)相同实验条件下,连续熵方法的测量精度最高,PKL方法的能力估计精度最低,其它方法的测量精度没有显著差异。     

Combining mixture distribution and multidimensional IRTree models for the measurement of extreme response styles

Personality constructs, attitudes and other non-cognitive variables are often measured using rating or Likert-type scales, which does not come without problems. Especially in low-stakes assessments, respondents may produce biased responses due to response styles (RS) that reduce the validity and comparability of the measurement. Detecting and correcting RS is not always straightforward because not all respondents show RS and the ones who do may not do so to the same extent or in the same direction. The present study proposes the combination of a multidimensional IRTree model with a mixture distribution item response theory model and illustrates the application of the approach using data from the Programme for the International Assessment of Adult Competencies (PIAAC). This joint approach allows for the differentiation between different latent classes of respondents who show different RS behaviours and respondents who show RS versus respondents who give (largely) unbiased responses. We illustrate the application of the approach by examining extreme RS and show how the resulting latent classes can be further examined using external variables and process data from computer-based assessments to develop a better understanding of response behaviour and RS.     

IRT框架下追踪数据的测量不变性分析——————以4至5岁儿童认知能力测验为例

本研究以4岁~5岁儿童认知能力测验为例,在IRT框架下探讨了如何进行追踪数据的测量不变性分析。分析模型采用项目间多维项目反应理论模型(between-item MIRT model)和项目内（within-item MIRT model）多维two-tier model,被试为来自全国的882名48个月的儿童,工具为自编4岁~5岁儿童认知能力测验。经测验水平 分析和项目水平分析,结果表明：(1)本文对追踪数据的测量不变性分析方法合理有效; (2)该测验在两个时间点上满足部分测量不变性要求,测验的潜在结构稳定; (3)“方位题”的区分度和难度参数都发生变化,另有4题难度参数出现浮动; (4)儿童在4岁~5岁期间认知能力总体呈快速发展趋势,能力增长显著。     

Reconstructing Paul Tillich's Anthropology: Multidimensional Life in Dialogue with Feminist Process Theology

Abstract: Influenced by feminist process theology, this article offers a difference‐oriented reconstruction of Paul Tillich's anthropology. The first section analyzes Tillich's anthropological reductionism at the “basis”(Grund ) of his unity‐oriented binary ontology and epistemology. The second section discloses Tillich's “reverse‐dynamics,” co‐present beside and despite of his anthropological “basis.” This concept of reverse‐dynamics prepares a new, pneumatologically and christologically deepened, “ground”(Grund ) for personhood and life as multidimensional.     

Scaling questions: asking and answering them in counselling1

Solution-focused counsellors use “scaling questions” to construct understandings of clients’ concerns and solutions to them. We examine how these questions are asked and answered, offering evidence of what is constructed from within counselling discourse. Also, clients and counsellors offer their retrospective accounts of their participation in question and answer sequences in their dialogues. We conclude by speaking to the implications we see from this research as it relates to collaborative and resourceful dialogue between counsellors and clients.     

A multidimensional item response model: Constrained latent class analysis using the gibbs sampler and posterior predictive checks

In this paper it will be shown that a certain class of constrained latent class models may be interpreted as a special case of nonparametric multidimensional item response models. The parameters of this latent class model will be estimated using an application of the Gibbs sampler. It will be illustrated that the Gibbs sampler is an excellent tool if inequality constraints have to be taken into consideration when making inferences. Model fit will be investigated using posterior predictive checks. Checks for manifest monotonicity, the agreement between the observed and expected conditional association structure, marginal local homogeneity, and the number of latent classes will be presented.This paper is supported by grant S40-645 of the Dutch Organization for Scientific Research (NWO).