Standard errors of fit indices using residuals in structural equation modeling

The asymptotic standard errors of the correlation residuals and Bentler's standardized residuals in covariance structures are derived based on the asymptotic covariance matrix of raw covariance residuals. Using these results, approximations of the asymptotic standard errors of the root mean square residuals for unstandardized or standardized residuals are derived by the delta method. Further, in mean structures, approximations of the asymptotic standard errors of residuals, standardized residuals and their summary statistics are derived in a similar manner. Simulations are carried out, which show that the asymptotic standard errors of the various types of residuals and the root mean square residuals in covariance, correlation and mean structures are close to actual ones.The author is indebted to the reviewers for their comments and suggestions which have led to an improvement of this work.     

Effect size, power, and sample size determination for structured means modeling and mimic approaches to between-groups hypothesis testing of means on a single latent construct

While effect size estimates, post hoc power estimates, and a priori sample size determination are becoming a routine part of univariate analyses involving measured variables (e.g., ANOVA), such measures and methods have not been articulated for analyses involving latent means. The current article presents standardized effect size measures for latent mean differences inferred from both structured means modeling and MIMIC approaches to hypothesis testing about differences among means on a single latent construct. These measures are then related to post hoc power analysis, a priori sample size determination, and a relevant measure of construct reliability.I wish to convey my appreciation to the reviewers and Associate Editor, whose suggestions extended and strengthened the article's content immensely, and to Ralph Mueller of The George Washington University for enhancing the clarity of its presentation.     

相似性判断和差异性判断的不对称性及其机制探索

本文阐述了相似性判断和差异性判断不对称性的相关研究。首先介绍了不对称性的发展及理论解释。其次,根据事件相关电位的研究结果,阐述了图-词信息的双编码模型对相似性判断的影响。接着分析和介绍了相似性判断的双编码过程及其时间进程。最后,作者提出有待深入研究的几个问题：（1）差异性策略在分类和推理中的应用;（2）相似性双编码过程的实证研究及其应用;（3）从发展认知神经科学的角度探讨不对称的认知神经机制。     

识字能力的单维性检验研究

本研究以义务教育阶段学生识字量测验为工具,综合运用探索性结构方程建模(ESEM)以及非参数项目反应理论中的摩根量表(Mokken量表)和DETECT分析方法,探讨了识字能力的维度。探索性结构方程建模结果显示,识字的单维性模型优于多维模型,多维的结果更多的体现出一个难度维度的特征,即字频的作用。Mokken量表分析结果显示,1~2年级和3~9年级测验更倾向于单维量表的特征。DETECT分析结果显示,两个测验的D值趋近于零,表明识字能力是单维能力。结合三种分析方法,识字能力具有单维性。     

结构实在论评析

The epistemological version of structural realism, proposed by Cao Tianyu, has great influence in the philosophy of science. Syntheses has published a special volume discussing the topic. Cao criticizes anti-realism, as well as the epistemic and ontic versions of structural realism. From the concepts of structure, ontology, and construction, he analyzes the objectivity of scientific theories as having five aspects: construction, historicity, holism, revision, and revolution. This paper systematically analyzes and comments on Cao's structural realism. The author agrees with his criticism of the under-determination thesis, is neutral to his argument against ontological discontinuity, and questions his universal language argument. Translated by Yu Jinlong from Ziran Bianzhengfa Yanjiu 自然辩证法研究 (Studies in Dialectics of Nature), 2006, (11): 34–38     

The Graded Response Differential Discrimination Model Accounting for Extreme Response Style

Extreme response style or, more generally, individual differences in response spacing have been shown to be an influential bias when analyzing questionnaire data. Recently a promising model adjusting for this bias — the differential discrimination model — has been proposed. An advantage to other related approaches is that the model can be fitted using standard structural equation modeling software. However, the model is designed for analyzing continuous item responses, whereas graded response formats are certainly more prominent in behavioral sciences. To resolve this limitation, the present article extends the differential discrimination model to analyzing graded responses. Empirical examples as well as a small simulation study are presented.     

Centering Predictor Variables in Three-Level Contextual Models

Hierarchical data are becoming increasingly complex, often involving more than two levels. Centering decisions in multilevel models are closely tied to substantive hypotheses and require researchers to be clear and cautious about their choices. This study investigated the implications of group mean centering (i.e., centering within context; CWC) and grand mean centering (CGM) of predictor variables in three-level contextual models. The goals were to (a) determine equivalencies in the means and variances across the centering options and (b) use the algebraic relationships between the centering choices to clarify the interpretation of the estimated parameters. We provide recommendations to assist the researcher in making centering decisions for analysis of three-level contextual models     

Searching for a common methodological ground for the study of politicians' perceived personality traits: A multilevel psycholexical approach

The aim of the three-stage psycholexical research was to systematize individual differences in voters’ perception of politicians’ personality traits and the differentiation dimensions of politicians’ images using the example of Ukraine. On the basis of 200 interviews, politicians’ personality lexicon was compiled and categorized. A representative sample of that lexicon was used in a study concerning the perception of several dozen politicians which allowed to identify four dimensions of politicians’ perceived personality traits at the individual and aggregate levels, distinct from the classic Big Five. Another study confirmed the stability of the structure of perception based on 2-level CFA and a strong relationship of personality image with preferences for politicians based on 2-level regression analysis.     

Emotionally enhanced memory for negatively arousing words: storage or retrieval advantage?

People typically remember emotionally negative words better than neutral words. Two experiments are reported that investigate whether emotionally enhanced memory (EEM) for negatively arousing words is based on a storage or retrieval advantage. Participants studied non-word–word pairs that either involved negatively arousing or neutral target words. Memory for these target words was tested by means of a recognition test and a cued-recall test. Data were analysed with a multinomial model that allows the disentanglement of storage and retrieval processes in the present recognition-then-cued-recall paradigm. In both experiments the multinomial analyses revealed no storage differences between negatively arousing and neutral words but a clear retrieval advantage for negatively arousing words in the cued-recall test. These findings suggest that EEM for negatively arousing words is driven by associative processes.