Exploring Factor Model Parameters across Continuous Variables with Local Structural Equation Models

Using an empirical data set, we investigated variation in factor model parameters across a continuous moderator variable and demonstrated three modeling approaches: multiple-group mean and covariance structure (MGMCS) analyses, local structural equation modeling (LSEM), and moderated factor analysis (MFA). We focused on how to study variation in factor model parameters as a function of continuous variables such as age, socioeconomic status, ability levels, acculturation, and so forth. Specifically, we formalized the LSEM approach in detail as compared with previous work and investigated its statistical properties with an analytical derivation and a simulation study. We also provide code for the easy implementation of LSEM. The illustration of methods was based on cross-sectional cognitive ability data from individuals ranging in age from 4 to 23 years. Variations in factor loadings across age were examined with regard to the age differentiation hypothesis. LSEM and MFA converged with respect to the conclusions. When there was a broad age range within groups and varying relations between the indicator variables and the common factor across age, MGMCS produced distorted parameter estimates. We discuss the pros of LSEM compared with MFA and recommend using the two tools as complementary approaches for investigating moderation in factor model parameters.     

The impact of emotions on stereotyping in workplace selection: The role of certainty appraisals

An appraisal tendency approach was adopted to explore the influence of emotional certainty on stereotyping and judgment in a workplace context. Across two studies, participants completed an emotional memory task designed to induce emotions representing two different levels of emotional certainty (certain versus uncertain). They then reviewed interview footage, a résumé, and qualifying criteria before rating a hypothetical job candidate’s personality and employability. Study 1 revealed that emotions high in certainty (compared to uncertainty) led to more favorable personality and employability ratings for attractive compared to unattractive candidates. Study 2 produced the same pattern of results for younger (compared to older) candidates. We conclude that certainty appraisals associated with temporary, incidental emotions are a useful predictor of the likelihood that stereotypes will be applied during decision making.     

Neo-pragmatism,morality, and the specification problem

Abstract

A defender of any view of moral language must explain how people with different moral views can be be talking to each other, rather than past each other. For expressivists this problem drastically constrains the search for the specific attitude expressed by, say, ‘immoral’. But cognitivists face a similar difficulty; they need to find a specific meaning for ‘immoral’ that underwrites genuine disagreement while accommodating the fact that different speakers have very different criteria for the use of that term. This paper explains how neo-pragmatism deals with this issue while avoiding problems that arise with existing expressivist and cognitivist solutions.     

Alternative Recipes for Life Satisfaction: Evidence from Five World Regions

In most cross-national research on Life Satisfaction (LS) an implicit assumption appears to be that the correlates of LS are the same the world over; ‘one size fits all’. Using data from the World Values Survey (1999–2014), we question this assumption by assessing the effects of differing personal values/life priorities on LS in five world regions: the West, Latin America, the Asian-Confucian region, ex-Communist Eastern Europe, and the Communist countries of China and Vietnam. We indicate that differing values - traditional family values, friendship and leisure values, materialistic values, political values, prosocial and environmental values, and religious values – are endorsed to varying degrees in different parts of the world, and vary in whether they have positive or negative effects on LS. Personal values provide the basis for alternative ‘recipes’ affecting LS. By ‘recipes’ we mean linked set of values, attitudes, behavioural choices and domain satisfactions that have a positive or negative effect on LS. We estimate structural equation models which indicate that differing values-based recipes help to account for large, unexpected differences between mean levels of LS in the five world regions, compared with the levels ‘predicted’ by GDP per capita. In particular, the high priority given to traditional family and religious recipes in Latin America helps to account for unexpectedly high LS in that region. Deficits in prosocial attitudes and behaviours partly account for low LS in ex-Communist Eastern Europe.

     

Measuring the speed of recognising facially expressed emotions

Faces provide identity- and emotion-related information-basic cues for mastering social interactions. Traditional models of face recognition suggest that following a very first initial stage the processing streams for facial identity and expression depart. In the present study we extended our previous multivariate investigations of face identity processing abilities to the speed of recognising facially expressed emotions. Analyses are based on a sample of N=151 young adults. First, we established a measurement model with a higher order factor for the speed of recognising facially expressed emotions (SRE). This model has acceptable fit without specifying emotion-specific relations between indicators. Next, we assessed whether SRE can be reliably distinguished from the speed of recognising facial identity (SRI) and found latent factors for SRE and SRI to be perfectly correlated. In contrast, SRE and SRI were both only moderately related to a latent factor for the speed of recognising non-face stimuli (SRNF). We conclude that the processing of facial stimuli-and not the processing of facially expressed basic emotions-is the critical component of SRE. These findings are at variance with suggestions of separate routes for processing facial identity and emotional facial expressions and suggest much more communality between these streams as far as the aspect of processing speed is concerned.     

Implicit word learning benefits from semantic richness: electrophysiological and behavioral evidence

Words differ considerably in the amount of associated semantic information. Despite the crucial role of meaning in language, it is still unclear whether and how this variability modulates language learning. Here, we provide initial evidence demonstrating that implicit learning in repetition priming is influenced by the amount of semantic features associated with a given word. Electroencephalographic recordings were obtained while participants performed a visual lexical decision task; the complete stimulus set was repeated once. Repetition priming effects on performance accuracy and the N400 component of the event-related brain potential were enhanced for words with many semantic features. These findings suggest a novel and important impact of the richness of semantic representations on learning and plasticity within the lexical-conceptual system; they are discussed in their relevance for assumptions concerning basic mechanisms underlying word learning.     

Mechanisms of developmental change in infant categorization

Computational models are tools for testing mechanistic theories of learning and development. Formal models allow us to instantiate theories of cognitive development in computer simulations. Model behavior can then be compared to real performance. Connectionist models, loosely based on neural information processing, have been successful in capturing a range of developmental phenomena, in particular on-line within-task category learning by young infants. Here we describe two new models. One demonstrates how age dependent changes in neural receptive field sizes can explain observed changes in on-line category learning between 3 and 10 months of age. The other aims to reconcile two conflicting views of infant categorization by focusing on the different task requirements of preferential looking and manual exploration studies. A dual-memory hypothesis posits that within-task category learning that drives looking time behaviors is based on a fast-learning memory system, whereas categorization based on background experience and assessed by paradigms requiring complex motor behavior relies on a second, slow-learning system. The models demonstrate how emphasizing the mechanistic causes of behaviors leads to discovery of deeper, more explanatory accounts of learning and development.     

Independence of data-driven and conceptually driven priming: the case of person recognition

A central tenet of current memory theories is the independence of data-driven and conceptually driven priming. Although these types of repetition priming have different functional properties, it has remained unclear whether they are independent and additive or interact with each other. Therefore, we orthogonally combined these priming types in two experiments requiring occupation judgments for celebrities, represented by their faces or names. In both experiments, the sum of the effects of separate data-driven priming and conceptually driven priming equaled the effect of the combination of these priming types. These findings demonstrate for the first time the independence of data-driven and conceptually driven priming and so confirm a central tenet of current memory theories. This independence may thus be an important element for the development of future overarching memory theories.