Inadequacy of recall as a basis for frequency knowledge.

Subjects studied a word list comprising varying numbers of words from distinct semantic categories. The category names (trees, colors, etc.) were then re-presented, and for each name subjects either recalled as many exemplars as they could or estimated how many had been included in the list (Experiments 1 and 2). Recall was not sufficiently informative about actual category sizes to account for performance in the frequency estimation task. Moreover, it remained insufficiently informative when efforts were made to induce a recall-estimate strategy by requiring overt recall prior to estimation (Experiments 3-5), by using very small categories (Experiment 4), and by not showing the category name at study (Experiment 5), even though it did allow a partial account of estimation when the category exemplars were individually cued (Experiment 6). It is concluded that the role of recall in frequency estimation is much exaggerated.     

A Bayesian Multi-Level Factor Analytic Model of Consumer Price Sensitivities Across Categories

Identifying price sensitive consumers is an important problem in marketing. We develop a Bayesian multi-level factor analytic model of the covariation among household-level price sensitivities across product categories that are substitutes. Based on a multivariate probit model of category incidence, this framework also allows the researcher to model overall price sensitivity (i.e., indicated by higher-order factor scores) as a function of household-level covariates. All model parameters are estimated simultaneously to circumvent the downward bias resulting from two-stage estimation. The modeling framework is illustrated using scanner panel data from multiple categories of instant coffee.     

Spatial categories and the estimation of location

Four experiments are reported in which people organize a space hierarchically when they estimate particular locations in that space. Earlier work showed that people subdivide circles into quadrants bounded at the vertical and horizontal axes, biasing their estimates towards prototypical diagonal locations within those spatial categories (Psychological Review 98 (1991) 352). In this work Huttenlocher, Hedges, and Duncan showed that the use of such spatial categories can increase the accuracy of estimation of inexactly represented locations. The stimulus locations we examined were uniformly distributed across the circle. In the present study we explore whether variation in the distribution of locations affects how the circle is categorized. Other things being equal, categories that capture high density regions in a stimulus space should contribute most to accuracy of estimation. However, precision of boundaries is also important to accuracy; with imprecise boundaries stimuli may be misclassified, leading to large errors in estimation. We found that people use the same spatial categories regardless of the distribution of the locations. We argue that this spatial organization nevertheless can maximize the accuracy of estimates because vertical and horizontal category boundaries are the most exact, minimizing misclassification of stimuli.     

Where am I looking? The accuracy of video-mediated gaze awareness

Participants worked in pairs, with one person gazing at a flat horizontal stimulus between them. The other participant estimated where the gazer was looking. Experiment 1 used linear scales as gaze targets. The mean root mean square error of estimation equates to 3.8 degrees of head-and-eye pan and 2.6 degrees of tilt. This small error of estimation was essentially the same in a video-mediated condition and in one in which a procedure that did not allow the estimator to see the head-and-eye movement to the target position was used. Experiment 2 obtained comparable gaze estimation performance in face-to-face and video-mediated conditions, using a combined pan-and-tilt grid. It is concluded that people are very good at estimating what someone else is looking at and that such estimations should be practical during video-mediated conversation.     

The structure of self‐reported emotional experiences: A mixed‐effects Poisson factor model

Multivariate count data are commonly analysed by using Poisson distributions with varying intensity parameters, resulting in a random‐effects model. In the analysis of a data set on the frequency of different emotion experiences we find that a Poisson model with a single random effect does not yield an adequate fit. An alternative model that requires as many random effects as emotion categories requires high‐dimensional integration and the estimation of a large number of parameters. As a solution to these computational problems, we propose a factor‐analytic Poisson model and show that a two‐dimensional factor model fits the reported data very well. Moreover, it yields a substantively satisfactory solution: one factor describing the degree of pleasantness and unpleasantness of emotions and the other factor describing the activation levels of the emotions. We discuss the incorporation of covariates to facilitate rigorous tests of the random‐effects structure. Marginal maximum likelihood methods lead to straight‐forward estimation of the model, for which goodness‐of‐fit tests are also presented.     

The role of experience in location estimation: Target distributions shift location memory biases

Research based on the Category Adjustment model concluded that the spatial distribution of target locations does not influence location estimation responses [Huttenlocher, J., Hedges, L., Corrigan, B., & Crawford, L. E. (2004). Spatial categories and the estimation of location. Cognition, 93, 75–97]. This conflicts with earlier results showing that location estimation is biased relative to the spatial distribution of targets [Spencer, J. P., & Hund, A. M. (2002). Prototypes and particulars: Geometric and experience-dependent spatial categories. Journal of Experimental Psychology: General, 131, 16–37]. Here, we resolve this controversy by using a task based on Huttenlocher et al. (Experiment 4) with minor modifications to enhance our ability to detect experience-dependent effects. Results after the first block of trials replicate the pattern reported in Huttenlocher et al. After additional experience, however, participants showed biases that significantly shifted according to the target distributions. These results are consistent with the Dynamic Field Theory, an alternative theory of spatial cognition that integrates long-term memory traces across trials relative to the perceived structure of the task space.     

Are Exact Calculation and Computational Estimation Categorically Different?

This study examined, through the problem‐size effect, whether exact calculation and computational estimation are categorically different. In Experiment 1, 26 teacher candidates, most of whom were female, Caucasian, and in their early 20s, estimated 27 randomly generated double‐digit multiplication problems. In Experiment 2, 44 similar participants estimated and calculated a common set of double‐digit multiplication problems. Analysis of reaction times and error rates indicates that the problem‐size effect holds true for exact calculation but not for estimation. In estimation, as problem size increases, reaction times do not increase, nor does the rate of unreasonable estimates. Instead, the difference between a factor's unit digit and the nearest ten to be rounded to was a primary contributor to the variance of reaction times. It is concluded that exact calculation and computational estimation are computationally, cognitively, and structurally different processes. Furthermore, it is suggested that estimation skills be given separate, dedicated attention in schools. Copyright © 2013 John Wiley & Sons, Ltd.     

基于GRM模型的BP神经网络参数估计

目前参数估计多采用统计方法,存在耗时长、要求被试样本容量大和项目数多等缺点。本文将BP神经网络和降维法相结合,对GRM的项目参数和考生能力参数进行估计。蒙特卡洛模拟结果显示：（1）不管是人多题少还是题多人少,该网络设计下的参数估计精度都较高;（2）可以应用到多个不同等级评分的参数估计中,甚至是超过15个等级的项目参数,估计精度也较高,这是其他参数估计方法所不可比拟的;（3）运行的时长和统计估计方法相比大大缩减。     

MIRT模型中多维能力及其相关矩阵估计的影响因素

多维项目反应理论因其模型本身的天然优势及其兼具因素分析与项目反应理论于一身的优点,而被广大研究者及应用者所重视.本研究在前人研究基础上,重点讨论MIRT多维能力及能力间相关矩阵的参数估计问题.研究采用Monte Carlo模拟方法进行,在三因素完全随机设计（4 ×3×3）下,使用MCMC算法,探讨测验维度数、维度间的相关大小和测验项目数三个因素对MIRT能力及其相关矩阵估计的影响.     

The use of autobiographical knowledge in age estimation

Event dates are not directly associated with memories, so the processes by which we maintain a sense of time and sequence in our autobiographical memories is of considerable interest. The present study examined participants’ reported age estimation strategies for childhood memories retrieved using a Galton-Crovitz cueing technique. The results indicate that all three categories of autobiographical knowledge in Conway and Pleydell-Pearce's (2000) self-memory system model—lifetime periods, general events, and event-specific details—support temporal inferences. However, participants most frequently used lifetime period knowledge to provide an initial age range, and event-specific knowledge was used to confirm or narrow the range of their estimated age.     

等级反应模型下计算机化自适应测验选题策略

计算机化自适应测验(CAT)中的选题策略,一直是国内外相关学者关注的问题。然而对多级评分的CAT的选题策略的研究却很少报导。本研究采用计算机模拟程序对等级反应模型(Graded Response Model)下CAT的四种选题策略进行研究。研究表明：等级难度值与当前能力估计值匹配选题策略的综合评价最高;在选题策略中增设 “影子题库”可以明显提高项目调用的均匀性;并且不同的项目参数分布或不同的能力估计方法都对CAT评价指标有影响     

One-minute time interval estimation as a novel potent indicator of emotional concerns in cancer patients prior to starting chemotherapy

Our study explored the potential relationship between time estimation and issues that lead to distress in cancer patients prior to starting chemotherapy. Time estimation was assessed in 375 chemonaïve patients with solid tumors by evaluating each subject’s prospective estimation of how quickly one minute passed compared to the actual time. The median estimated value (40 s) was used to stratify the patients into the two categories of fast and slow time estimation. The National Comprehensive Cancer Network Distress Thermometer (DT) and Problem List (PL) were used at the beginning of treatment to evaluate levels of distress and patient concerns. A fast time estimation correlated significantly with gender and items reported in the emotional domain on the PL. Females exhibited significantly faster time estimation than males. Patients who reported fear, worry and loss of interest in usual activities estimated the one-minute interval significantly faster than patients who did not report such items. In the multivariate logistic regression model, patients who experienced fast time estimation had a higher risk of reporting items in the emotional domain. Time estimation is a novel potent indicator of emotional concerns on the PL. This test is an easily performed, time-saving, nonintrusive, ultrashort screening tool that is suitable even for patients who are not willing to reveal their emotional status via direct questionnaires.

     

ThurCatD: A tool for analyzing ratings on an ordinal category scale

An algorithm for analyzing ordinal scaling results is described. Frequency data on ordinal categories are modeled for unidimensional psychological attributes according to Thurstone’s judgment scaling model. The algorithm applies maximum likelihood estimation of model parameters. The Cramér-Rao bounds of the standard errors of the estimated parameters are calculated, and a stress measure and a goodness-of-fit measure are supplied.     

基于分部评分模型思路的多级评分认知诊断模型开发

基于分部评分模型的思路, 本文提出了一般化的分部评分认知诊断模型(General Partial Credit Diagnostic Model, GPCDM), 与国际上已有的基于分部评分模型思路的多级评分模型GDM (von Davier, 2008)和PC-DINA (de la Torre, 2012)相比, GPCDM的Q矩阵定义更加灵活, 项目参数的约束条件更少。Monte Carlo实验研究表明, GPCDM模型的参数估计精度指标RMSE介于[0.015, 0.043], 表明估计精度尚可; TIMSS (2007)实证数据应用研究表明, 与GDM和PC-DINA模型相比, GPCDM与该数据的拟合度更好, 并且使用GPCDM分析该数据的诊断效果也更优。总之, 本研究提供了一种约束条件更少、功能更为强大的多级评分认知诊断模型。     

Bayesian Gaussian distributional regression models for more efficient norm estimation

A test score on a psychological test is usually expressed as a normed score, representing its position relative to test scores in a reference population. These typically depend on predictor(s) such as age. The test score distribution conditional on predictors is estimated using regression, which may need large normative samples to estimate the relationships between the predictor(s) and the distribution characteristics properly. In this study, we examine to what extent this burden can be alleviated by using prior information in the estimation of new norms with Bayesian Gaussian distributional regression. In a simulation study, we investigate to what extent this norm estimation is more efficient and how robust it is to prior model deviations. We varied the prior type, prior misspecification and sample size. In our simulated conditions, using a fixed effects prior resulted in more efficient norm estimation than a weakly informative prior as long as the prior misspecification was not age dependent. With the proposed method and reasonable prior information, the same norm precision can be achieved with a smaller normative sample, at least in empirical problems similar to our simulated conditions. This may help test developers to achieve cost-efficient high-quality norms. The method is illustrated using empirical normative data from the IDS-2 intelligence test.     

一种多级评分的认知诊断模型：P-DINA模型的开发

当前绝大多数认知诊断计量模型仅适用于0-1评分数据资料, 大大限制了认知诊断在实际中的应用, 也限制了认知诊断的进一步推广和发展。本文对具有较好发展前景的DINA模型进行拓展, 开发出适合多种评分(含0-1二级评分和多级评分)数据资料的P-DINA模型, 同时采用MCMC算法实现模型参数的估计, 并对该模型性能进行研究。结果表明：(1)本文开发的P-DINA模型无论是在无结构型属性层级关系下还是在结构型属性层级关系下, 参数估计的精度均较高, 参数估计的稳健性较强, 说明开发的P-DINA模型基本合理、可行。(2)P-DINA模型可采用MCMC算法实现参数估计, 且参数估计的精度较高。(3)整体来看, 无结构型属性层级关系和结构型属性层级关系下, P-DINA模型在项目参数的估计精度上两者基本相当; 但在被试属性判准率(MMR和PMR)上无结构型属性层级关系表现的稍差一些。(4)无结构型属性阶层关系下：模型诊断的属性个数越多, 参数 估计的精度越差、属性诊断的正确率(MMR和PMR)越低, 但参数 的估计精度越好; 若想保证属性模式判准率在80%以上, 建议诊断的属性个数不宜超过7个。总之, 本研究为拓展认知诊断在教育学和心理学中的应用提供了一种新方法、新模型。     

单维项目因素分析：CCFA与IRT估计方法的比较

当观测指标变量为二分分类数据时,传统的因素分析方法不再适用。作者简要回顾了SEM框架下的分类数据因素分析模型和IRT框架下的测验题目和潜在能力的关系模型,并对两种框架下主要采用的参数估计方法进行了总结。通过两个模拟研究,比较了SEM框架下GLSc和MGLSc估计方法与IRT框架下MML/EM估计方法的差异。研究结果表明：（1）三种方法中,GLSc得到参数估计的偏差最大,MGLSc和MML/EM估计方法相差不大;（2）随着样本量增大,各种项目参数估计的精度均提高;（3）项目因素载荷和难度估计的精度受测验长度的影响;（4）项目因素载荷和区分度估计的精度受总体因素载荷（区分度）高低的影响;（5）测验项目中阈值的分布会影响参数估计的精度,其中受影响最大的是项目区分度。（6）总体来看,SEM框架下的项目参数估计精度较IRT框架下项目参数估计的精度高。此外,文章还将两种方法在实际应用中应该注意的问题提供了一些建议。     

Sufficiency and Conditional Estimation of Person Parameters in the Polytomous Rasch Model

Rasch models are characterised by sufficient statistics for all parameters. In the Rasch unidimensional model for two ordered categories, the parameterisation of the person and item is symmetrical and it is readily established that the total scores of a person and item are sufficient statistics for their respective parameters. In contrast, in the unidimensional polytomous Rasch model for more than two ordered categories, the parameterisation is not symmetrical. Specifically, each item has a vector of item parameters, one for each category, and each person only one person parameter. In addition, different items can have different numbers of categories and, therefore, different numbers of parameters. The sufficient statistic for the parameters of an item is itself a vector. In estimating the person parameters in presently available software, these sufficient statistics are not used to condition out the item parameters. This paper derives a conditional, pairwise, pseudo-likelihood and constructs estimates of the parameters of any number of persons which are independent of all item parameters and of the maximum scores of all items. It also shows that these estimates are consistent. Although Rasch’s original work began with equating tests using test scores, and not with items of a test, the polytomous Rasch model has not been applied in this way. Operationally, this is because the current approaches, in which item parameters are estimated first, cannot handle test data where there may be many scores with zero frequencies. A small simulation study shows that, when using the estimation equations derived in this paper, such a property of the data is no impediment to the application of the model at the level of tests. This opens up the possibility of using the polytomous Rasch model directly in equating test scores.     

Parametric and nonparametric bootstrap methods for meta-analysis

In a meta-analysis, the unknown parameters are often estimated using maximum likelihood, and inferences are based on asymptotic theory. It is assumed that, conditional on study characteristics included in the model, the between-study distribution and the sampling distributions of the effect sizes are normal. In practice, however, samples are finite, and the normality assumption may be violated, possibly resulting in biased estimates and inappropriate standard errors. In this article, we propose two parametric and two nonparametric bootstrap methods that can be used to adjust the results of maximum likelihood estimation in meta-analysis and illustrate them with empirical data. A simulation study, with raw data drawn from normal distributions, reveals that the parametric bootstrap methods and one of the nonparametric methods are generally superior to the ordinary maximum likelihood approach but suffer from a bias/precision tradeoff. We recommend using one of these bootstrap methods, but without applying the bias correction.     

Retrospective duration estimation of public events

In three experiments, we investigated subjects' retrospective estimation of the duration of publicly reported events such as, for example, the Falkland's war. In Experiment 1, duration estimates were found to be positively correlated with event knowledge, in keeping with Ornstein's (1969) model of duration estimation. Event duration was, however, generally underestimated, suggesting that the relationship between event knowledge and estimated duration might reflect an increase in estimation accuracy. Other results of Experiment 1 were consistent with this interpretation and suggested that the duration estimates might be largely reconstructed. In Experiment 2, duration estimates of specific events and general categories of events were found to be highly correlated, and the subjects in Experiment 3 indicated that they used knowledge of the general characteristic of different types of events to estimate event duration. Overall, reallife duration estimates appear to be based on a combination of specific event information and knowledge derived about that category of event.