scholarly journals A Psychometric Network Perspective on the Validity and Validation of Personality Trait Questionnaires

2020 ◽  
Vol 34 (6) ◽  
pp. 1095-1108 ◽  
Author(s):  
Alexander P. Christensen ◽  
Hudson Golino ◽  
Paul J. Silvia
Keyword(s):  
Personality Trait ◽  
Latent Variable ◽  
European Association ◽  
Structural Phase ◽  
External Validation ◽  
Network Models ◽  
Complementary Information ◽  
Future Directions ◽  
Personality Psychology ◽  
Structural Consistency

This article reviews the causal implications of latent variable and psychometric network models for the validation of personality trait questionnaires. These models imply different data generating mechanisms that have important consequences for the validity and validation of questionnaires. From this review, we formalize a framework for assessing the evidence for the validity of questionnaires from the psychometric network perspective. We focus specifically on the structural phase of validation, where items are assessed for redundancy, dimensionality, and internal structure. In this discussion, we underline the importance of identifying unique personality components (i.e. an item or set of items that share a unique common cause) and representing the breadth of each trait's domain in personality networks. After, we argue that psychometric network models have measures that are statistically equivalent to factor models but we suggest that their substantive interpretations differ. Finally, we provide a novel measure of structural consistency, which provides complementary information to internal consistency measures. We close with future directions for how external validation can be executed using psychometric network models. © 2020 European Association of Personality Psychology

scholarly journals A Psychometric Network Perspective on the Validity and Validation of Personality Trait Questionnaires

2019 ◽  
Author(s):  
Alexander P. Christensen ◽  
Hudson Golino ◽  
Paul Silvia
Keyword(s):  
Personality Trait ◽  
Latent Variable ◽  
Structural Phase ◽  
External Validation ◽  
Network Models ◽  
Factor Models ◽  
Complementary Information ◽  
Future Directions ◽  
Common Cause ◽  
Structural Consistency

This article reviews the causal implications of latent variable and psychometric network models for the validation of personality trait questionnaires. These models imply different data generating mechanisms that have important consequences for the validity and validation of questionnaires. From this review, we formalize a framework for assessing the evidence for the validity of questionnaires from the psychometric network perspective. We focus specifically on the structural phase of validation where items are assessed for redundancy, dimensionality, and internal structure. In this discussion, we underline the importance of identifying unique personality components (i.e., an item or set of items that share a unique common cause) and representing the breadth of each trait’s domain in personality networks. After, we argue that psychometric network models have measures that are statistically equivalent to factor models, but suggest that their substantive interpretations differ. Finally, we provide a novel measure of structural consistency, which provides complementary information to internal consistency measures. We close with future directions for how external validation can be executed using psychometric network models.

The Country'S Crime Rate Moderates the Relation between Authoritarian Predispositions and the Manifestations of Authoritarianism: A Multilevel, Multinational Study

2014 ◽  
Vol 28 (1) ◽  
pp. 14-24 ◽  
Author(s):  
Michele Roccato ◽  
Alessio Vieno ◽  
Silvia Russo
Keyword(s):  
Crime Rate ◽  
European Association ◽  
Crime Rates ◽  
Negative Attitudes ◽  
Future Directions ◽  
Personality Psychology ◽  
European Values Survey ◽  
European Values ◽  
High Crime ◽  
Racial Intolerance

We performed a multilevel, multinational test of Stenner's model on authoritarianism using the 2008 European Values Survey dataset (N = 55 199, nested in 38 nations). We focussed on the effects exerted on four authoritarian manifestations (racial intolerance, political intolerance, negative attitudes towards immigrants, and moral intolerance) by the cross–level interaction between participants’ authoritarian predispositions (assessed in terms of childrearing values) and their country's crime rate. Associations between authoritarian predispositions and racial intolerance, political intolerance, negative attitudes towards immigrants, and moral intolerance were significantly stronger among participants living in countries characterised by high crime rates than those among participants living in countries with low crime rates. Limitations, implications, and future directions of this study are discussed. Copyright © 2013 European Association of Personality Psychology.

scholarly journals Towards More Rigorous Personality Trait–Outcome Research

2016 ◽  
Vol 30 (4) ◽  
pp. 292-303 ◽  
Author(s):  
René Mõttus
Keyword(s):  
Personality Traits ◽  
Personality Trait ◽  
Outcome Research ◽  
European Association ◽  
Causal Inferences ◽  
Personality Psychology ◽  
Factor Loadings ◽  
Personality Research ◽  
Trait Level

Much of personality research attempts to identify causal links between personality traits and various types of outcomes. I argue that causal interpretations require traits to be seen as existentially and holistically real and the associations to be independent of specific ways of operationalizing the traits. Among other things, this means that, to the extents that causality is to be ascribed to such holistic traits, items and facets of those traits should be similarly associated with specific outcomes, except for variability in the degrees to which they reflect the traits (i.e. factor loadings). I argue that, before drawing causal inferences about personality trait–outcome associations, the presence of this condition should be routinely tested by, for example, systematically comparing the outcome associations of individual items or facets, or sampling different indicators for measuring the same purported traits. Existing evidence suggests that observed associations between personality traits and outcomes at least sometimes depend on which particular items or facets have been included in trait operationalizations, calling trait–level causal interpretations into question. However, this has rarely been considered in the literature. I argue that when outcome associations are specific to facets, they should not be generalized to traits. Furthermore, when the associations are specific to particular items, they should not even be generalized to facets. Copyright © 2016 European Association of Personality Psychology

scholarly journals Collective Narcissism Predicts Hypersensitivity to In–group Insult and Direct and Indirect Retaliatory Intergroup Hostility

2016 ◽  
Vol 30 (6) ◽  
pp. 532-551 ◽  
Author(s):  
Agnieszka Golec de Zavala ◽  
Müjde Peker ◽  
Rita Guerra ◽  
Tomasz Baran
Keyword(s):  
European Union ◽  
Economic Crisis ◽  
European Association ◽  
External Validation ◽  
The European Union ◽  
Personality Psychology ◽  
European Economic ◽  
Definition Of ◽  
Polish Government

Results of five studies (N = 1596) linked collective narcissism—a belief in in–group exaggerated greatness contingent on external validation—to direct and indirect, retaliatory hostility in response to situations that collective narcissists perceived as insulting to the in–group but which fell well beyond the definition of an insult. In Turkey, collective narcissists responded with schadenfreude to the European economic crisis after feeling humiliated by the Turkish wait to be admitted to the European Union (Study 1). In Portugal, they supported hostile actions towards Germans and rejoiced in the German economic crisis after perceiving Germany's position in the European Union as more important than the position of Portugal (Study 2). In Poland, they supported hostile actions towards the makers of a movie they found offensive to Poland (Studies 3 and 5) and responded with direct and indirect hostility towards a celebrity whose jokes about the Polish government they found offensive (Study 4). Comparisons with self–positivity and in–group positivity indices and predictors of intergroup hostility indicated that collective narcissism is the only systematic predictor of hypersensitivity to in–group insult followed by direct and indirect, retaliatory intergroup hostility. Copyright © 2016 European Association of Personality Psychology

Conclusions and Future Directions for the Study of Accurate Personality Judgment

2020 ◽  
Author(s):  
Tera D. Letzring
Keyword(s):  
Standardized Tests ◽  
Personality Trait ◽  
Training Programs ◽  
Future Research ◽  
Research Topics ◽  
Theoretical Frameworks ◽  
Future Directions ◽  
Personality Judgment ◽  
Exciting Time ◽  
And Training

This chapter identifies several well-established findings and overarching themes within personality trait accuracy research, and highlights especially promising directions for future research. Topics include (1) theoretical frameworks for accuracy, (2) moderators of accuracy and the context or situation in which judgments are made, (3) the important consequences of accuracy, (4) interventions and training programs to increase judgmental ability and judgability, (5) the generalizability of previous findings, and (6) standardized tests of the accuracy of judging personality traits. The chapter ends by stating that it is an exciting time to be a researcher studying the accuracy of personality trait judgments.

scholarly journals Investigating the Structure of Intelligence Using Latent Variable and Psychometric Network Modeling: A Commentary and Reanalysis

2021 ◽  
Vol 9 (1) ◽  
pp. 8
Author(s):  
Christopher J. Schmank ◽  
Sara Anne Goring ◽  
Kristof Kovacs ◽  
Andrew R. A. Conway
Keyword(s):  
Cognitive Processes ◽  
Latent Variable ◽  
Network Modeling ◽  
Network Models ◽  
Mental Ability ◽  
Variable Model ◽  
General Mental Ability ◽  
Theories Of Intelligence ◽  
Psychological Theories ◽  
Model Preference

In a recent publication in the Journal of Intelligence, Dennis McFarland mischaracterized previous research using latent variable and psychometric network modeling to investigate the structure of intelligence. Misconceptions presented by McFarland are identified and discussed. We reiterate and clarify the goal of our previous research on network models, which is to improve compatibility between psychological theories and statistical models of intelligence. WAIS-IV data provided by McFarland were reanalyzed using latent variable and psychometric network modeling. The results are consistent with our previous study and show that a latent variable model and a network model both provide an adequate fit to the WAIS-IV. We therefore argue that model preference should be determined by theory compatibility. Theories of intelligence that posit a general mental ability (general intelligence) are compatible with latent variable models. More recent approaches, such as mutualism and process overlap theory, reject the notion of general mental ability and are therefore more compatible with network models, which depict the structure of intelligence as an interconnected network of cognitive processes sampled by a battery of tests. We emphasize the importance of compatibility between theories and models in scientific research on intelligence.

Personality in Action: Assessing Personality to Identify an ‘Ideal’ Conscientious Response Type with Two Different Behavioural Tasks

2020 ◽  
Vol 34 (5) ◽  
pp. 808-825
Author(s):  
Gabriela Gniewosz ◽  
Tuulia M. Ortner ◽  
Thomas Scherndl
Keyword(s):  
European Association ◽  
Cognitive Styles ◽  
Personality Characteristics ◽  
Self Report ◽  
Subjective Response ◽  
Response Type ◽  
Personality Psychology ◽  
Different Types ◽  
Typological Approach ◽  
Related Response

Performance on achievement tests is characterized by an interplay of different individual attributes such as personality traits, motivation or cognitive styles. However, the prediction of individuals’ performance from classical self–report personality measures obtained during large and comprehensive aptitude assessments is biased by, for example, subjective response tendencies. This study goes beyond by using behavioural data based on two different types of tasks, requiring different conscientious–related response behaviours. Moreover, a typological approach is proposed, which includes different behavioural indicators to obtain information on complex personality characteristics. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology

scholarly journals Does Cooperation in the Laboratory Reflect the Operation of A Broad Trait?

2019 ◽  
Vol 33 (1) ◽  
pp. 89-103 ◽  
Author(s):  
William H.B. McAuliffe ◽  
Daniel E. Forster ◽  
Eric J. Pedersen ◽  
Michael E. McCullough
Keyword(s):  
European Association ◽  
Dictator Game ◽  
Bifactor Model ◽  
Trust Game ◽  
General Factor ◽  
Valid Measure ◽  
Personality Psychology ◽  
Economic Games ◽  
Social Settings ◽  
Self Assessments

The Dictator Game, a face valid measure of altruism, and the Trust Game, a face valid measure of trust and trustworthiness, are among the most widely used behavioural measures in human cooperation research. Researchers have observed considerable covariation among these and other economic games, leading them to assert that there exists a general human propensity to cooperate that varies in strength across individuals and manifests itself across a variety of social settings. To formalize this hypothesis, we created an S–1 bifactor model using 276 participants’ Dictator Game and Trust Game decisions. The general factor had significant, moderate associations with self–reported and peer–reported altruism, trust, and trustworthiness. Thus, the positive covariation among economic games is not reducible to the games’ shared situational features. Two hundred participants returned for a second session. The general factor based on Dictator Game and Trust Game decisions from this session did not significantly predict self–reported and peer–reported cooperation, suggesting that experience with economic games causes them to measure different traits from those that are reflected in self–assessments and peer–assessments of cooperativeness. © 2018 European Association of Personality Psychology

Toward scientifically useful quantitative models of psychopathology: The importance of a comparative approach

2010 ◽  
Vol 33 (2-3) ◽  
pp. 163-164 ◽  
Author(s):  
Robert F. Krueger ◽  
Colin G. DeYoung ◽  
Kristian E. Markon
Keyword(s):  
Latent Variable ◽  
Network Models ◽  
Latent Variable Models ◽  
Comparative Approach ◽  
Quantitative Models

AbstractCramer et al. articulate a novel perspective on comorbidity. However, their network models must be compared with more parsimonious latent variable models before conclusions can be drawn about network models as plausible accounts of comorbidity. Latent variable models have proven generative in studying psychopathology and its external correlates, and we doubt network models will prove as useful for psychopathology research.

scholarly journals Factor or Network Model? Predictions From Neural Networks

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Alexander P. Christensen ◽  
Keyword(s):  
Neural Networks ◽  
Network Model ◽  
Latent Variable ◽  
Random Network ◽  
Network Models ◽  
Small World ◽  
Small World Network ◽  
Monte Carlo Simulation Study ◽  
Psychological Phenomena ◽  
The Neural Networks

The nature of associations between variables is important for constructing theory about psychological phenomena. In the last decade, this topic has received renewed interest with the introduction of psychometric network models. In psychology, network models are often contrasted with latent variable (e.g., factor) models. Recent research has shown that differences between the two tend to be more substantive than statistical. One recently developed algorithm called the Loadings Comparison Test (LCT) was developed to predict whether data were generated from a factor or small-world network model. A significant limitation of the current LCT implementation is that it's based on heuristics that were derived from descriptive statistics. In the present study, we used artificial neural networks to replace these heuristics and develop a more robust and generalizable algorithm. We performed a Monte Carlo simulation study that compared neural networks to the original LCT algorithm as well as logistic regression models that were trained on the same data. We found that the neural networks performed as well as or better than both methods for predicting whether data were generated from a factor, small-world network, or random network model. Although the neural networks were trained on small-world networks, we show that they can reliably predict the data-generating model of random networks, demonstrating generalizability beyond the trained data. We echo the call for more formal theories about the relations between variables and discuss the role of the LCT in this process.

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