From eye movement to cognition: Toward a general framework of inference comment on Liechty et al., 2003

Liechty, Pieters & Wedel (2003) developed a hidden Markov Model (HMM) to identify the states of an attentional process in an advertisement viewing task. This work is significant because it demonstrates the benefits of stochastic modeling and Bayesian estimation in making inferences about cognitive processes based on eye movement data. One limitation of the proposed approach is that attention is conceptualized as an autonomous random process that is affected neither by the overall layout of the stimulus nor by the visual information perceived during the current fixation. An alternative model based on the input-output hidden Markov model (IOHMM; Bengio, 1999) is suggested as an extension of the HMM. The need for further studies that validate the HMM classification results is also discussed.     

Data, model, conclusion, doing it again

This paper explores the robustness of conclusions from a statistical model against variations in model choice (rather than variations in random sampling and random assignment to treatments, which are the usual variations covered by inferential statistics). After the problem formulation in section 1, section 2 presents an example from Box and Tiao in which variation in parent distribution is modeled for a one sample location problem. An adaptive Bayesian procedure permits to use a weighted mixture of parent distributions rather than choosing just one, such as a normal or a uniform distribution.In section 3 similar considerations are applied to an event history model for the influence of education and gender on age at first marriage, but here the conclusions are hardly influenced by the choice of the duration distribution. In section 4 a brief discussion of model choice in factor analysis and structural equation models is followed by a more elaborate treatment of the choice of integer valued slopes for item response functions in the OPLM model which is an extension of the Rasch model. A modest simulation study suggests that Adaptive Bayesian Modeling with a mixture of sets of slopes works better than fixing one set of postulated slopes.The paper concludes with some remarks on the roles and sources of prior distributions followed by a short epilogue which argues that simultaneous consideration of a class of models for the same data is sometimes superior to exclusively analyzing the data under one specific model chosen from such a class.This article is based on the Presidential Address Ivo W. Molenaar gave on June 20, 1998 at the 1998 Annual Meeting of the Psychometric Society held at the University of Illinois in Champaign, Illinois. Thanks is given to John Wiley & Sons and George C. Tiao for granting permission to reprint three figures from the book George C. Tiao wrote with George E. P. Box titled Bayesian Inference in Statistical Analysis.—EditorThanks are due to Anne Boomsma, Jeffrey Hoogland, Mark Huisman, Tom Snijders, Marijtje Van Duijn, and Norman Verhelst for suggesting improvements and/or assisting with data analyses.     

A latent class approach to fitting the weighted Euclidean model,clascal

A weighted Euclidean distance model for analyzing three-way proximity data is proposed that incorporates a latent class approach. In this latent class weighted Euclidean model, the contribution to the distance function between two stimuli is per dimension weighted identically by all subjects in the same latent class. This model removes the rotational invariance of the classical multidimensional scaling model retaining psychologically meaningful dimensions, and drastically reduces the number of parameters in the traditional INDSCAL model. The probability density function for the data of a subject is posited to be a finite mixture of spherical multivariate normal densities. The maximum likelihood function is optimized by means of an EM algorithm; a modified Fisher scoring method is used to update the parameters in the M-step. A model selection strategy is proposed and illustrated on both real and artificial data.The second author is supported as Bevoegdverklaard Navorser of the Belgian Nationaal Fonds voor Wetenschappelijk Onderzoek.     

A latent class unfolding model for analyzing single stimulus preference ratings

A multidimensional unfolding model is developed that assumes that the subjects can be clustered into a small number of homogeneous groups or classes. The subjects that belong to the same group are represented by a single ideal point. Since it is not known in advance to which group of class a subject belongs, a mixture distribution model is formulated that can be considered as a latent class model for continuous single stimulus preference ratings. A GEM algorithm is described for estimating the parameters in the model. The M-step of the algorithm is based on a majorization procedure for updating the estimates of the spatial model parameters. A strategy for selecting the appropriate number of classes and the appropriate number of dimensions is proposed and fully illustrated on some artificial data. The latent class unfolding model is applied to political science data concerning party preferences from members of the Dutch Parliament. Finally, some possible extensions of the model are discussed.The first author is supported as Bevoegdverklaard Navorser of the Belgian Nationaal Fonds voor Wetenschappelijk Onderzoek. Part of this paper was presented at the Distancia meeting held in Rennes, France, June 1992.     

INTERVENTIONS TO REDUCE HIGH-VOLUME PORTABLE HEADSETS: “TURN DOWN THE SOUND!”

Two studies examined effects of interventions to reduce noise levels from portable stereo headphones. Study 1 examined the effectiveness of warning signs posted in and nearby public elevators with 567 passengers possessing a portable headphone (total N = 7,811). During a 9-day baseline, the mean percentage of headphones played at an observer-audible level was 85%. During a subsequent 6-day warning sign phase, the mean percentage of audible headphones declined to 59%, which increased to a mean of 76% during a second baseline phase (5 days). Study 2 assessed the impact of a student confederate who lowered his or her observer-audible headphone volume at the polite request of a second student confederate. Of the 4,069 elevator passengers, 433 possessed a portable headset. The mean percentage of observer-audible headphones during a 4-day baseline was 85%. Subsequently, a 5-day modeling intervention reduced audible volumes to a mean of 46%. During a second baseline phase of 4 days, the mean level was 77%, and during reintroduction of the modeling phase (9 days) the mean level was 42%. The modeling intervention was significantly more effective with women (53% compliance) than men (29% compliance).     

An extension of the rating scale model with an application to the measurement of change

The polytomous unidimensional Rasch model with equidistant scoring, also known as the rating scale model, is extended in such a way that the item parameters are linearly decomposed into certain basic parameters. The extended model is denoted as the linear rating scale model (LRSM). A conditional maximum likelihood estimation procedure and a likelihood-ratio test of hypotheses within the framework of the LRSM are presented. Since the LRSM is a generalization of both the dichotomous Rasch model and the rating scale model, the present algorithm is suited for conditional maximum likelihood estimation in these submodels as well. The practicality of the conditional method is demonstrated by means of a dichotomous Rasch example with 100 items, of a rating scale example with 30 items and 5 categories, and in the light of an empirical application to the measurement of treatment effects in a clinical study.Work supported in part by the Fonds zur Förderung der Wissenschaftlichen Forschung under Grant No. P6414.     

三维虚拟空间中转头选中远离和靠近运动目标的操作特性差异

通过转头选中运动目标是虚拟现实(VR)中的常见操作,然而运动目标包含远离和靠近运动,确定两类操作的时间特性差异对设计高效的用户接口有重要的意义。本研究选取17名被试在VR中通过转头将球体光标快速准确地放入水平运动的球体目标内,并改变初始距离、目标容差和目标速度。总时间结果显示,远离运动的操作难度更大,初始距离和目标容差对远离和靠近运动的影响相似,目标速度对两类运动的影响相反。进一步将光标的移动过程划分为加速、减速和调整阶段,结果发现,远离运动的加速和减速时间大于靠近运动,但是两类运动的调整时间接近,并且只有目标容差对两类运动的影响一致。最后构建了总时间与三因素的函数模型,成功解释了两类运动的操作时间特性。本研究证明了远离与靠近运动具有不同的操作时间特性,为两类运动的独立交互设计提供了重要参考。     

Dynamics and moderating factors of esport participation and loneliness: A daily diary study

The purpose of this study was to examine the association between esport participation and loneliness, as well as its moderating factors. Chinese college students (N = 216) self-reported their esport playing time and degree of loneliness each day immediately before bedtime for four consecutive weeks. The findings revealed that as playing time increased, students did not experience reduced sense of loneliness during playing esport, but they experienced a temporary and intensified feeling of loneliness the same day following gameplay. Students with higher general loneliness tended to feel more after-game loneliness associated with increased esport participation. Students with higher obsessive passion about esport tended to experience more loneliness (both in-game and after-game) associated with increased esport participation. Students with greater coping motivation about esport tended to experience more in-game loneliness associated with previous increased esport participation. Students who played esport less often with friends in person, or with more escape motivation toward esport, tended to increase esport participation time more following previous increased after-game loneliness. The findings suggested that college students should avoid utilizing esport to achieve a sense of belonging and should be cautious of the loneliness-inducing effect after gameplay. A healthy level of loneliness can be maintained by playing esport more with friends in person, learning strategies to avoid obsessive passion, coping motivation, and escape motivation towards esport.     

Temperament and behaviour problems in children: A multilevel analysis of cross-cultural differences

Early temperament attributes have been linked to emerging behaviour problems and significant long-term consequences; however, these relations are rarely examined cross-culturally. The present study addresses this gap, employing multilevel modelling to explain within- and between-culture variances with respect to temperament predicting a spectrum of behaviour problems across 14 nations from the Joint Effort Toddler Temperament Consortium (JETTC). A total of 865 children between 17 and 40 months, with approximately equal age distribution across this developmental period and about equivalent representation of genders, were recruited from 14 nations. Greater negative emotionality was associated with more internalizing problems, whereas higher surgency and effortful control predicted fewer internalizing difficulties. Controlling for age and gender, temperament explained significant within- and between-culture variances in internalizing and externalizing problems (at the broad-band and fine-grained levels), as well as sleep problems. For internalizing difficulties, temperament accounted for more between-culture variance. In contrast, for externalizing difficulties, temperament accounted more for how individuals within the same culture differed from their same-culture counterparts. The within-culture findings suggest universal patterns of temperament-problem relations, informing cultural adaptation of interventions; between-culture findings enhance understanding of the implications of the cultural niche for normative behaviour and adjustment.     

Mixture-modelling-based Bayesian MH-RM algorithm for the multidimensional 4PLM

Several recent works have tackled the estimation issue for the unidimensional four-parameter logistic model (4PLM). Despite these efforts, the issue remains a challenge for the multidimensional 4PLM (M4PLM). Fu et al. (2021) proposed a Gibbs sampler for the M4PLM, but it is time-consuming. In this paper, a mixture-modelling-based Bayesian MH-RM (MM-MH-RM) algorithm is proposed for the M4PLM to obtain the maximum a posteriori (MAP) estimates. In a comparison of the MM-MH-RM algorithm to the original MH-RM algorithm, two simulation studies and an empirical example demonstrated that the MM-MH-RM algorithm possessed the benefits of the mixture-modelling approach and could produce more robust estimates with guaranteed convergence rates and fast computation. The MATLAB codes for the MM-MH-RM algorithm are available in the online appendix.