Confirmatory Factor Analysis (CFA), Exploratory Structural Equation Modeling (ESEM), and Set-ESEM: Optimal Balance Between Goodness of Fit and Parsimony

Abstract

CFAs of multidimensional constructs often fail to meet standards of good measurement (e.g., goodness-of-fit, measurement invariance, and well-differentiated factors). Exploratory structural equation modeling (ESEM) represents a compromise between exploratory factor analysis’ (EFA) flexibility, and CFA/SEM’s rigor and parsimony, but lacks parsimony (particularly in large models) and might confound constructs that need to be kept separate. In Set-ESEM, two or more a priori sets of constructs are modeled within a single model such that cross-loadings are permissible within the same set of factors (as in Full-ESEM) but are constrained to be zero for factors in different sets (as in CFA). The different sets can reflect the same set of constructs on multiple occasions, and/or different constructs measured within the same wave. Hence, Set-ESEM that represents a middle-ground between the flexibility of traditional-ESEM (hereafter referred to as Full-ESEM) and the rigor and parsimony of CFA/SEM. Thus, the purposes of this article are to provide an overview tutorial on Set-ESEM, juxtapose it with Full-ESEM, and to illustrate its application with simulated data and diverse “real” data applications with accessible, heuristic explanations of best practice.     

Measuring time perspective in adolescents: Can you get the right answer by asking the wrong questions?

Time perspective continues to evolve as a psychological construct. The extant literature suggests that higher future orientation and lower present orientation are associated with better developmental outcomes. However, the extant literature also suggests that issues remain with the measurement of the construct. Recently, a 25-item version of the Zimbardo Time Perspective Inventory (ZTPI-25) was suggested for use based on high internal consistency estimates and good discriminant validity of scores in a sample of Italian adolescents. However, the genesis of this scale is uncertain. The present study examined the factorial validity, reliability, and concurrent validity of ZTPI-25 scores in Slovenian, American, and British adolescents. Results revealed satisfactory concurrent validity based on correlations with measures used in the development of the full ZTPI. However, internal consistency and factorial validity of scores were unsatisfactory. The present study questions the use of the ZTPI-25 with adolescents in the context of conceptual and measurement issues more broadly.     

Generation and evaluation of user tailored responses in multimodal dialogue

When people engage in conversation, they tailor their utterances to their conversational partners, whether these partners are other humans or computational systems. This tailoring, or adaptation to the partner takes place in all facets of human language use, and is based on a mental model or a user model of the conversational partner. Such adaptation has been shown to improve listeners’ comprehension, their satisfaction with an interactive system, the efficiency with which they execute conversational tasks, and the likelihood of achieving higher level goals such as changing the listener’s beliefs and attitudes. We focus on one aspect of adaptation, namely the tailoring of the content of dialogue system utterances for the higher level processes of persuasion, argumentation and advice-giving. Our hypothesis is that algorithms that adapt content for these processes, according to a user model, will improve the usability, efficiency, and effectiveness of dialogue systems. We describe a multimodal dialogue system and algorithms for adaptive content selection based on multi-attribute decision theory. We demonstrate experimentally the improved efficacy of system responses through the use of user models to both tailor the content of system utterances and to manipulate their conciseness.     

Estimation of Controlled Direct Effects in Longitudinal Mediation Analyses with Latent Variables in Randomized Studies

Abstract

In a randomized study with longitudinal data on a mediator and outcome, estimating the direct effect of treatment on the outcome at a particular time requires adjusting for confounding of the association between the outcome and all preceding instances of the mediator. When the confounders are themselves affected by treatment, standard regression adjustment is prone to severe bias. In contrast, G-estimation requires less stringent assumptions than path analysis using SEM to unbiasedly estimate the direct effect even in linear settings. In this article, we propose a G-estimation method to estimate the controlled direct effect of treatment on the outcome, by adapting existing G-estimation methods for time-varying treatments without mediators. The proposed method can accommodate continuous and noncontinuous mediators, and requires no models for the confounders. Unbiased estimation only requires correctly specifying a mean model for either the mediator or the outcome. The method is further extended to settings where the mediator or outcome, or both, are latent, and generalizes existing methods for single measurement occasions of the mediator and outcome to longitudinal data on the mediator and outcome. The methods are utilized to assess the effects of an intervention on physical activity that is possibly mediated by motivation to exercise in a randomized study.     

Interpretation-based processing: a unified theory of semantic sentence comprehension

We present interpretation-based processing—a theory of sentence processing that builds a syntactic and a semantic representation for a sentence and assigns an interpretation to the sentence as soon as possible. That interpretation can further participate in comprehension and in lexical processing and is vital for relating the sentence to the prior discourse. Our theory offers a unified account of the processing of literal sentences, metaphoric sentences, and sentences containing semantic illusions. It also explains how text can prime lexical access. We show that word literality is a matter of degree and that the speed and quality of comprehension depend both on how similar words are to their antecedents in the preceding text and how salient the sentence is with respect to the preceding text. Interpretation-based processing also reconciles superficially contradictory findings about the difference in processing times for metaphors and literals. The theory has been implemented in ACT-R [Anderson and Lebiere, The Atomic Components of Thought, Lawrence Erlbaum Associates Publishers, Mahwah, NJ, 1998].     

WOMEN'S CAREER DECISION-MAKING PROCESS

No abstract available for this article.     

And justice for all: Revisiting the Global Belief in a Just World Scale

The Global Belief in a Just World Scale (GBJWS) has been widely used in measuring the Belief in a Just World (BJW) personality trait. Despite its widespread application across the social sciences, the validity of this scale has not been sufficiently tested in the literature. In this research, the authors examine the internal and external validity of the GBJWS using both standard correlational analyses and structural equation modeling (SEM). Specifically, the authors test the concurrent validity, internal consistency, unidimensional structure, convergent validity, and both measurement and latent mean invariance of the scale across gender and culture. The results of a pilot study suggest strong concurrent validity of the GBJWS with other BJW scales, and the findings of the two main studies support the internal and external validity of GBJWS across gender and culture. The authors’ results further show an overall greater level of BJW of Chinese individuals compared to Americans. The present research provides a much needed investigation of the validity of the GBJWS, and answers calls for research examining the scale’s utility across different populations.     

Statistical models for the induction and use of selectional preferences

Selectional preferences have a long history in both generative and computational linguistics. However, since the publication of Resnik's dissertation in 1993, a new approach has surfaced in the computational linguistics community. This new line of research combines knowledge represented in a pre‐defined semantic class hierarchy with statistical tools including information theory, statistical modeling, and Bayesian inference. These tools are used to learn selectional preferences from examples in a corpus. Instead of simple sets of semantic classes, selectional preferences are viewed as probability distributions over various entities. We survey research that extends Resnik's initial work, discuss the strengths and weaknesses of each approach, and show how they together form a cohesive line of research.     

Relationship between resilience,stress and burnout among civil servants in Beijing,China: Mediating and moderating effect analysis

This study aimed to explore the mediating and moderating effect in the relationship between resilience, stress and burnout among civil servants of Beijing, China. A cross-sectional study was conducted among civil servants in Beijing. Totally 541 civil servants completed a self-report questionnaire including three scales measuring civil servants’ resilience, stress and burnout. The data were analyzed with correlation, multiple regression and structural equation modeling. The results revealed that work stress rather than life and health stress could significantly predict burnout. Resilience played a partial mediating role between work stress and burnout, that is, work stress had both a direct and an indirect, via resilience, impact on burnout. Work stress played a partial mediating role between resilience and burnout, thus, resilience could prevent the development of burnout by relieving work stress, in addition to directly relieving it. Moreover, resilience was a moderator between work stress and burnout, and it could serve as a buffer to mitigate the adverse effects of work stress. These results suggest that resilience could be a positive personality trait for alleviating or eliminating work stress and combating burnout of civil servants of Beijing.     

The minimal self hypothesis

For millennia self has been conjectured to be necessary for consciousness. But scant empirical evidence has been adduced to support this hypothesis. Inconsistent explications of “self” and failure to design apt experiments have impeded progress. Advocates of phenomenological psychiatry, however, have helped explicate “self,” and employed it to explain some psychopathological symptoms. In those studies, “self” is understood in a minimalist sense, sheer “for-me-ness.” Unfortunately, explication of the “minimal self” (MS) has relied on conceptual analysis, and applications to psychopathology have been hermeneutic, allowing for many degrees of interpretive latitude. The result is that MS’s current scientific status is analogous to that of the “atom,” at the time when “atom” was just beginning to undergo transformation from a philosophical to a scientific concept. Fortunately, there is now an opportunity to promote a similar transformation for “MS.” Discovery of the brain’s Default Mode Network (DMN) opened the door to neuroimaging investigations of self. Taking the DMN and other forms of intrinsic activity as a starting point, an empirical foothold can be established, one that spurs experimental research and that enables extension of research into multiple phenomena. New experimental protocols that posit “MS” can help explain phenomena hitherto not thought to be related to self, thereby hastening development of a mature science of self. In particular, targeting phenomena wherein consciousness is lost and recovered, as in some cases of Unresponsive Wakefulness Syndrome (UWS), allow for design of neuroimaging probes that enable detection of MS during non-conscious states. These probes, as well as other experimental protocols applied to NREM Sleep, General Anesthesia (GA), and the waking state, provide some evidence to suggest that not only can self and consciousness dissociate, MS might be a necessary precondition for conscious experience. Finally, these findings have implications for the science of consciousness: it has been suggested that “levels of consciousness” (LoC) is not a legitimate concept for the science of consciousness. But because we have the conceptual and methodological tools with which to refine investigations of MS, we have the means to identify a possible foundation—a bifurcation point—for consciousness, as well as the means by which to measure degrees of distance from that foundation. These neuroimaging investigations of MS position us to better assess whether LoC has a role to play in a mature science of consciousness.