工作家庭间跨界增益:逻辑主线与模型

已有工作家庭界面研究主要立足于冲突视角,近年来部分研究开始从积极视角揭示工作家庭关系的本质。工作家庭增益强调角色资源的跨界渗溢有助提升个体另一角色表现和生活品质的程度。工作家庭资源会增强个体心理资源,进而影响体验工作家庭间的跨界增益,资源的累积循环与工作家庭增益互为持续保障,跨界增益的程度受到工作家庭边界特征的调节影响。论证和提出了"角色资源累积-个体心理因素改变-跨界增益-角色评价与投入"的逻辑主线,以此构建工作家庭间角色资源跨界增益模型。     

恋人概念威胁启动削弱自我和恋人面孔优势效应:来自眼动研究的证据

采用眼动记录技术和恋人概念威胁启动范式探讨自我和恋人面孔优势效应的产生和维持过程。结果发现:与概念非威胁启动条件下相比,概念威胁启动条件下,被试搜索恋人面孔时的兴趣区个数和搜索自我面孔时的平均眼跳次数与搜索陌生人面孔时比差异变得不显著;恋人面孔与陌生人面孔在兴趣区内总注视时间上的差异变得不显著。结果表明,自我与恋人面孔存在注意的优先捕获和维持优势,恋人概念的威胁启动会减少对恋人的关注,证明了建立恋人的积极概念是恋人面孔优势效应产生和维持的重要原因。     

Polytomous multilevel testlet models for testlet‐based assessments with complex sampling designs

A pplications of standard item response theory models assume local independence of items and persons. This paper presents polytomous multilevel testlet models for dual dependence due to item and person clustering in testlet‐based assessments with clustered samples. Simulation and survey data were analysed with a multilevel partial credit testlet model. This model was compared with three alternative models – a testlet partial credit model (PCM), multilevel PCM, and PCM – in terms of model parameter estimation. The results indicated that the deviance information criterion was the fit index that always correctly identified the true multilevel testlet model based on the quantified evidence in model selection, while the Akaike and Bayesian information criteria could not identify the true model. In general, the estimation model and the magnitude of item and person clustering impacted the estimation accuracy of ability parameters, while only the estimation model and the magnitude of item clustering affected the item parameter estimation accuracy. Furthermore, ignoring item clustering effects produced higher total errors in item parameter estimates but did not have much impact on the accuracy of ability parameter estimates, while ignoring person clustering effects yielded higher total errors in ability parameter estimates but did not have much effect on the accuracy of item parameter estimates. When both clustering effects were ignored in the PCM, item and ability parameter estimation accuracy was reduced.     

Two simple approximations to the distributions of quadratic forms

Many test statistics are asymptotically equivalent to quadratic forms of normal variables, which are further equivalent to with z_i being independent and following N(0,1). Two approximations to the distribution of T have been implemented in popular software and are widely used in evaluating various models. It is important to know how accurate these approximations are when compared to each other and to the exact distribution of T. The paper systematically studies the quality of the two approximations and examines the effect of the λ_i and the degrees of freedom d by analysis and Monte Carlo. The results imply that the adjusted distribution for T can be as good as knowing its exact distribution. When the coefficient of variation of the λ_i is small, the rescaled statistic is also adequate for practical model inference. But comparing T_R against will inflate type I errors when substantial differences exist among the λ_i, especially, when d is also large.     

Bayesian analysis of mixtures in structural equation models with non‐ignorable missing data

Structural equation models (SEMs) have become widely used to determine the interrelationships between latent and observed variables in social, psychological, and behavioural sciences. As heterogeneous data are very common in practical research in these fields, the analysis of mixture models has received a lot of attention in the literature. An important issue in the analysis of mixture SEMs is the presence of missing data, in particular of data missing with a non‐ignorable mechanism. However, only a limited amount of work has been done in analysing mixture SEMs with non‐ignorable missing data. The main objective of this paper is to develop a Bayesian approach for analysing mixture SEMs with an unknown number of components and non‐ignorable missing data. A simulation study shows that Bayesian estimates obtained by the proposed Markov chain Monte Carlo methods are accurate and the Bayes factor computed via a path sampling procedure is useful for identifying the correct number of components, selecting an appropriate missingness mechanism, and investigating various effects of latent variables in the mixture SEMs. A real data set on a study of job satisfaction is used to demonstrate the methodology.     

Determinants of Standard Errors of MLEs in Confirmatory Factor Analysis

This paper studies changes of standard errors (SE) of the normal-distribution-based maximum likelihood estimates (MLE) for confirmatory factor models as model parameters vary. Using logical analysis, simplified formulas and numerical verification, monotonic relationships between SEs and factor loadings as well as unique variances are found. Conditions under which monotonic relationships do not exist are also identified. Such functional relationships allow researchers to better understand the problem when significant factor loading estimates are expected but not obtained, and vice versa. What will affect the likelihood for Heywood cases (negative unique variance estimates) is also explicit through these relationships. Empirical findings in the literature are discussed using the obtained results.     

论《淮南子》的墨子观

《淮南子》对墨子持有复杂的政治认识与态度,这在秦汉思想史上具有一定的代表性。从黄老道家的根本立场出发,“批墨”是《淮南子》政治思想的基本主张,但与此同时,《淮南子》也内在地显示出“尊墨”的政治情怀,进而试图对墨子政治思想有所借鉴和汲取,达到“融墨”之理论目的。对待墨子及其政治思想的历史态度,既凸显出《淮南子》立足黄老,融通诸子的博大精神,也彰显出墨子在秦汉政治思想发展中独特的历史影响。