Out-of-bag Prediction Error: A Cross Validation Index for Generalized Structured Component Analysis

Cross validation is a useful way of comparing predictive generalizability of theoretically plausible a priori models in structural equation modeling (SEM). A number of overall or local cross validation indices have been proposed for existing factor-based and component-based approaches to SEM, including covariance structure analysis and partial least squares path modeling. However, there is no such cross validation index available for generalized structured component analysis (GSCA) which is another component-based approach. We thus propose a cross validation index for GSCA, called Out-of-bag Prediction Error (OPE), which estimates the expected prediction error of a model over replications of so-called in-bag and out-of-bag samples constructed through the implementation of the bootstrap method. The calculation of this index is well-suited to the estimation procedure of GSCA, which uses the bootstrap method to obtain the standard errors or confidence intervals of parameter estimates. We empirically evaluate the performance of the proposed index through the analyses of both simulated and real data.     

Four Covariance Structure Models for Canonical Correlation Analysis: A COSAN Modeling Approach

The mathematical connection between canonical correlation analysis (CCA) and covariance structure analysis was first discussed through the Multiple Indicators and Multiple Causes (MIMIC) approach. However, the MIMIC approach has several technical and practical challenges. To address these challenges, a comprehensive COSAN modeling approach is proposed. Specifically, we define four COSAN-CCA models to correspond with four possible combinations of the data to be analyzed and the unique parameters to be estimated. In terms of the data, one can analyze either the unstandardized or standardized variables. In terms of the unique parameters, one can estimate either the weights or loadings. Besides the unique parameters of each COSAN-CCA model, all four COSAN-CCA models also estimate the canonical correlations as their common parameters. Taken together, the four COSAN-CCA models provide the correct point estimates and standard error estimates for all commonly used CCA parameters. Two numeric examples are used to compare the standard error estimates obtained from the MIMIC approach and the COSAN modeling approach. Moreover, the standard error estimates from the COSAN modeling approach are validated by a simulation study and the asymptotic theory. Finally, software implementation and future extensions are discussed.     

Item response theory analyses of the Delis-Kaplan Executive Function System card sorting subtest

In the current study, we examined the dimensionality of the 16-item Card Sorting subtest of the Delis-Kaplan Executive Functioning System assessment in a sample of 264 native English-speaking children between the ages of 9 and 15 years. We also tested for measurement invariance for these items across age and gender groups using item response theory (IRT). Results of the exploratory factor analysis indicated that a two-factor model that distinguished between verbal and perceptual items provided the best fit to the data. Although the items demonstrated measurement invariance across age groups, measurement invariance was violated for gender groups, with two items demonstrating differential item functioning for males and females. Multigroup analysis using all 16 items indicated that the items were more effective for individuals whose IRT scale scores were relatively high. A single-group explanatory IRT model using 14 non-differential item functioning items showed that for perceptual ability, females scored higher than males and that scores increased with age for both males and females; for verbal ability, the observed increase in scores across age differed for males and females. The implications of these findings are discussed.     

多维项目反应理论补偿性模型参数估计:基于广义回归神经网络集合

运用广义回归神经网络(GRNN)方法对小样本多维项目反应理论(MIRT)补偿性模型的项目参数进行估计,尝试解决传统参数估计方法样本数量要求较大的问题。MIRT双参数Logistic补偿模型被设置为二级计分的二维模型。首先,模拟二维能力参数、项目参数值与考生作答矩阵。其次,把通过主成分分析得到的前两个因子在每个题目上的载荷作为区分度的初始值以及题目通过率作为难度的初始值,这两个指标的初始值作为神经网络的输入。集成100个神经网络,其输出值的均值作为MIRT的项目参数估计值。最后,设置2×2种(能力相关水平:0.3和0.7; 两种估计方法:GRNN和MCMC方法)实验处理,对GRNN和MCMC估计方法的返真性进行比较。结果表明,小样本的情况下,基于GRNN集成方法的参数估计结果优于MCMC方法。     

Romantic Crushes Promote Variety‐Seeking Behavior

Consumers making repeat consumption choices often need to decide whether to stick to their favorite option or to select something different. Understanding the situational factors that influence their willingness to seek more or less variety in consumption is of both theoretical and practical importance. The current research proposes that a salient relationship state—romantic crush—can increase consumers' variety‐seeking tendency in unrelated consumption situations. Building on the compensatory consumption literature, we suggest that the lack of reciprocal response in the romantic crush experience may lower consumers' sense of control in the romantic relationship. Therefore, they are motivated to restore their sense of control by making more varied choices in consumption domains. Five studies provide support for this hypothesis. In line with our control‐restoration account, the effect disappears when consumers' sense of control is boosted via other means. Moreover, the effect is specific to the experience of a romantic crush and cannot be generalized to other types of romantic relationship (e.g., initial stage of love).     

The effects of physical contact and decision type on moral decision making: A study of harm to save moral behavior

This study examined the relationship between physical contact and decision type in predicting “harm to save” behavior. Participants were assigned to making either a judgment or a choice involving moral dilemmas. All participants were presented with dilemmas that either required or did not require having physical contact with potential victims. Participants were asked to decide whether to sacrifice fewer people to save more (utilitarian responses) or not to do so and thus more people would die (deontological responses). The study sample included 345 participants who completed a set of self‐report measures. Results indicated an interaction between physical contact and decision type. In the choice condition only, participants reported significantly less utilitarian responses to the dilemmas that required having physical contact with the person to be harmed than to dilemmas that did not require physical contact. This difference was not found in the judgment condition. These results contribute to a greater understanding of the nature and potential malleability of human morality.     

Maximus the Confessor and the Problem of Participation

In defining the theological problem of participation as the question of how created beings, namely human beings, can participate (μ?θεξι?) in the transcendent Uncreated God towards deification (θ?ωσι?) without a pantheistic blurring of essences, this article examines the Christologically intuitive way in which Maximus the Confessor (580–662) would have responded. Specifically, Maximus’ Cyrilline Chalcednonianism, featuring an unconfused perichoretic union between Christ's two natures in his hypostatic union, serves directly as an apologetic and hermeneutic for humanity's and creation's participation in God. In addition, taking into account the scholarly debate over Maximus’ understanding of the relationship between the Logos and the logoi, it is argued that this indirectly provides a second Christological way forward to resolve the problem at hand, particularly when the two types of logoi (that ‘of being’ and that ‘of virtue’) are correctly distinguished. Insofar as the Logos and the logoi, not to mention the notions of participation and deification, were viewed by Maximus through his Cyrilline Chalcedonian lens, his Cyrilline Chalcednonian Christology was ultimately his answer to the theological problem of participation.     

Experimental Power for Indirect Effects in Group-randomized Studies with Group-level Mediators

Mediation analyses have provided a critical platform to assess the validity of theories of action across a wide range of disciplines. Despite widespread interest and development in these analyses, literature guiding the design of mediation studies has been largely unavailable. Like studies focused on the detection of a total or main effect, an important design consideration is the statistical power to detect indirect effects if they exist. Understanding the sensitivity to detect indirect effects is exceptionally important because it directly influences the scale of data collection and ultimately governs the types of evidence group-randomized studies can bring to bear on theories of action. However, unlike studies concerned with the detection of total effects, literature has not established power formulas for detecting multilevel indirect effects in group-randomized designs. In this study, we develop closed-form expressions to estimate the variance of and the power to detect indirect effects in group-randomized studies with a group-level mediator using two-level linear models (i.e., 2-2-1 mediation). The results suggest that when carefully planned, group-randomized designs may frequently be well positioned to detect mediation effects with typical sample sizes. The resulting power formulas are implemented in the R package PowerUpR and the PowerUp!-Mediator software (causalevaluation.org).     

Help yourself by helping others: The joint impact of group member organizational citizenship behaviors and group cohesiveness on group member objective task performance change

This paper examines how a group member's individual‐targeted citizenship behavior (OCBI) and organization‐targeted citizenship behavior (OCBO) interact with a salient group‐level contextual variable, group cohesiveness, to foster positive change for that group member, starting with job self‐efficacy change, and followed by objective task performance change. Over a span of 6 months, we engaged in multilevel, multisource, multistage data collection and surveyed 587 members in 83 work groups. Our results indicate that a group member's OCBI, in comparison with OCBO, is more positively related to his or her job self‐efficacy change. Group cohesiveness was found to attenuate the relationship between a group member's OCBI and job self‐efficacy change, and conversely, to accentuate the relationship between a group member's OCBO and job self‐efficacy change. Furthermore, a group member's job self‐efficacy change mediated the interactive effects of the group member's OCBI and group cohesiveness (as well as the group member's OCBO and group cohesiveness) on his or her objective task performance change.     

Influence of plastic strain localisation on the mechanical properties of metal matrix composites

The aim of the present study is to reveal the most critical underlying factor influencing the mechanical properties of metal matrix composites (MMCs). It is shown that the mechanical properties of MMCs are essentially governed by the degree of strain localisation during plastic deformation. In other words, the MMCs exhibit superior mechanical performance only if the strain localisation is obviously inhibited and the accumulated stresses can be effectively transferred out. The work provides a new perspective in guiding the design of next-generation high-performance MMCs by suppressing the strain localisation as far as possible.