Cross-National Comparison of Attitudes Toward Fathers' and Mothers' Participation in Household Tasks and Childcare

The purpose of this study was to explore attitudes toward the division of fathers' and mothers' participation in childcare/household tasks through a multilevel modeling approach. Data from the Euro-barometer surveys, including over 10,000 respondents from 13 European countries, were used. Respondents' attitudes were related to several individual-and macro-level factors. At the individual level (based on a separate regression equation for each country), it was found that respondents were most likely to hold egalitarian attitudes toward household work and childcare when they were younger, female, and politically liberal. At the macro level, countries' United Nations ratings on women's empowerment, Gross National Product, and cultural individualism were related to egalitarian attitudes. Study implications, strengths and weaknesses, and suggestions for future research are discussed.     

基于空间分割的手写输入系统的用户绩效模型

为定量估计与提高基于空间分割的手写输入系统用户绩效 ,运用Fitts定律及离散变量的数学期望等方法推导了用户绩效的数学模型。实验验证了该模型在具体界面中能较好地拟合用户在 8次 (8× 2 4字 )训练后的实际操作绩效。应用该模型可较好地拟合用户使用手写系统完成抄写任务的时间、推算输入系统某些参数的最佳设置值 ;并发现当输入系统的其它参数为定值时 ,缩短用户单字手写时间会比缩短系统识别时间能更有效地提高用户绩效。     

贝叶斯结构方程模型及其研究现状

在心理学研究中结构方程模型(Structural Equation Modeling, SEM)被广泛用于检验潜变量间的因果效应, 其估计方法有频率学方法(如, 极大似然估计)和贝叶斯方法两类。近年来由于贝叶斯统计的流行及其在结构方程建模中易于处理小样本、缺失数据及复杂模型等方面的优势, 贝叶斯结构方程模型发展迅速, 但其在国内心理学领域的应用不足。主要介绍了贝叶斯结构方程模型的方法基础和优良特性, 及几类常用的贝叶斯结构方程模型及其应用现状, 旨在为应用研究者介绍新的研究工具。     

小学低年级儿童口语词汇知识的发展轨迹及其影响因素

以149名小学生为研究对象, 对其口语词汇知识进行了历时3年的5次追踪测试, 采用潜变量增长模型探索了小学1~3年级学生汉语口语词汇知识的发展轨迹, 并考察了语音意识、同形语素意识、复合语素意识和家庭社会经济地位对口语词汇知识发展轨迹的影响。结果发现：(1) 1~3年级学生口语词汇知识发展轨迹呈曲线形式, 其中前两年呈线性发展, 三年级时呈加速发展, 发展速度是前期发展的两倍, 起始水平和发展速度均存在显著的个体差异; (2)语音意识、同形语素意识、复合语素意识和家庭社会经济地位均可以正向预测学生口语词汇知识的起始水平; (3)只有同形语素意识和家庭社会经济地位可以正向预测学生口语词汇知识的发展速度。     

Quantifying the psychopathic stare: Automated assessment of head motion is related to antisocial traits in forensic interviews

Clinicians have long noted that individuals with high psychopathic traits exhibit unique interpersonal style often observable during forensic interviews. Here we develop an automated approach for quantifying head dynamics during video-recorded naturalistic clinical interviews. We expected head dynamics would be related to psychopathic traits. As predicted, dwell times indicate that those with higher levels of psychopathic traits are characterized by more stationary head positions, focused directly towards the camera/interviewer, than were individuals low in psychopathic traits. These associations were primarily driven by developmental/antisocial features of psychopathy, indicating that those with severe and life-course persistent antisocial behavior exhibit more rigid and focused orienting of their head during interpersonal communication. These results encourage more research into the automated quantification of behavioral manifestations of personality to support clinical observations that psychopaths exhibit unique qualities in non-verbal interpersonal communication.     

A Computational Evaluation of Two Models of Retrieval Processes in Sentence Processing in Aphasia

Can sentence comprehension impairments in aphasia be explained by difficulties arising from dependency completion processes in parsing? Two distinct models of dependency completion difficulty are investigated, the Lewis and Vasishth (2005) activation-based model and the direct-access model (DA; McElree, 2000). These models' predictive performance is compared using data from individuals with aphasia (IWAs) and control participants. The data are from a self-paced listening task involving subject and object relative clauses. The relative predictive performance of the models is evaluated using k-fold cross-validation. For both IWAs and controls, the activation-based model furnishes a somewhat better quantitative fit to the data than the DA. Model comparisons using Bayes factors show that, assuming an activation-based model, intermittent deficiencies may be the best explanation for the cause of impairments in IWAs, although slowed syntax and lexical delayed access may also play a role. This is the first computational evaluation of different models of dependency completion using data from impaired and unimpaired individuals. This evaluation develops a systematic approach that can be used to quantitatively compare the predictions of competing models of language processing.     

A zero-bounded model of operant demand

Contemporary approaches for evaluating the demand for reinforcers use either the Exponential or the Exponentiated model of operant demand, both derived from the framework of Hursh and Silberberg (2008). This report summarizes the strengths and complications of this framework and proposes a novel implementation. This novel implementation incorporates earlier strengths and resolves existing shortcomings that are due to the use of a logarithmic scale for consumption. The Inverse Hyperbolic Sine (IHS) transformation is reviewed and evaluated as a replacement for the logarithmic scale in models of operant demand. Modeling consumption in the “log₁₀-like” IHS scale reflects relative changes in consumption (as with a log scale) and accommodates a true zero bound (i.e., zero consumption values). The presence of a zero bound obviates the need for a separate span parameter (i.e., k) and the span of the model may be more simply defined by maximum demand at zero price (i.e., Q₀). Further, this reformulated model serves to decouple the exponential rate constant (i.e., α) from variations in span, thus normalizing the rate constant to the span of consumption in IHS units and permitting comparisons when spans vary. This model, called the Zero-bounded Exponential (ZBE), is evaluated using simulated and real-world data. The direct reinstatement ZBE model showed strong correspondence with empirical indicators of demand and with a normalization of α (ZBEn) across empirical data that varied in reinforcing efficacy (dose, time to onset of peak effects). Future directions in demand curve analysis are discussed with recommendations for additional replication and exploration of scales beyond the logarithm when accommodating zero consumption data.     

A Method of Correcting Estimation Failure in Latent Differential Equations with Comparisons to Kalman Filtering

Abstract

Studies have used the latent differential equation (LDE) model to estimate the parameters of damped oscillation in various phenomena, but it has been shown that correct, non-zero parameter estimates are only obtained when the latent series exhibits little or no process noise. Consequently, LDEs are limited to modeling deterministic processes with measurement error rather than those with random behavior in the true latent state. The reasons for these limitations are considered, and a piecewise deterministic approximation (PDA) algorithm is proposed to treat process noise outliers as functional discontinuities and obtain correct estimates of the damping parameter. Comprehensive, random-effects simulations were used to compare results with those obtained using a state-space model (SSM) based on the Kalman filter. The LDE with the PDA algorithm (LDEPDA) successfully recovered the simulated damping parameter under a variety of conditions when process noise was present in the latent state. The LDEPDA had greater precision and accuracy than the SSM when estimating parameters from data with sparse jump discontinuities, but worse performance for diffusion processes overall. All three methods were applied to a sample of postural sway data. The basic LDE estimated zero damping, while the LDEPDA and SSM estimated moderate to high damping. The SSM estimated the smallest standard errors for both frequency and damping parameter estimates.     

Exploring orthographic neighborhood size effects in a computational model of Chinese character naming

Orthographic neighborhood (N) size effects have been extensively studied in English consistently producing a facilitatory effect in word naming tasks. In contrast, several recent studies on Chinese character naming have demonstrated an inhibitory effect of neighborhood size. Response latencies tend to be inhibited by inconsistent characters with large neighborhoods relative to small neighborhoods. These differences in neighborhood effects between languages may depend on the characteristics (depth) of the mapping between orthography and phonology. To explore this, we first conducted a behavioral experiment to investigate the relationship between neighborhood size, consistency and reading response. The results showed an inhibitory effect of neighborhood size for inconsistent characters but a facilitatory effect for consistent characters. We then developed two computational models based on parallel distributed processing principles to try and capture the nature of the processing that leads to these results in Chinese character naming. Simulations using models based on the triangle model of reading indicated that consistency and neighborhood size interact with the division of labor between semantics and phonology to produce these effects.