Modeling the Structure of the Triarchic Psychopathy Measure: Conceptual, Empirical, and Analytic Considerations

2019 ◽  
Vol 33 (4) ◽  
pp. 470-496 ◽  
Author(s):  
Antonella Somma ◽  
Serena Borroni ◽  
Laura E. Drislane ◽  
Christopher J. Patrick ◽  
Andrea Fossati
Keyword(s):  
Factor Structure ◽  
Structural Equation ◽  
Factor Model ◽  
Community Dwelling ◽  
Least Square ◽  
Equation Modeling ◽  
General Factor ◽  
Specific Content ◽  
Using Data ◽  
Three Factor

This study sought to characterize the factor structure of the Triarchic Psychopathy Measure (TriPM) using data from a sample of 1,082 community-dwelling Italian adults. Exploratory structural equation modeling (ESEM) was used to compare the fit of a bifactor model for each TriPM scale, in which specific-content factors were specified along with a general factor, with the fit of a single, general-factor model. Robust weighted least square (WLSMV) ESEM supported a bifactor latent structure of the TriPM items for all individual scales. When we jointly factor analyzed the 58 TriPM items, a WLSMV ESEM three-factor structure showed adequate fit; the three ESEM factors were akin to TriPM Boldness, Meanness, and Disinhibition theoretical dimensions, respectively, and could be effectively replicated across gender subgroups. Our findings support the three-factor structure of TriPM items, at least in Italian community-dwelling adults, and provide further evidence for the construct validity of the TriPM.

Working Memory, Mental Prospection, Time Orientation, and Cognitive Insight

2013 ◽  
Vol 34 (3) ◽  
pp. 159-169 ◽  
Author(s):  
Sevtap Cinan ◽  
Aslı Doğan
Keyword(s):  
Working Memory ◽  
Structural Equation ◽  
Factor Model ◽  
Time Orientation ◽  
Equation Modeling ◽  
Cognitive Insight ◽  
Confirmatory Factor ◽  
Negative Effect ◽  
Positive Effect ◽  
Three Factor

This research is new in its attempt to take future time orientation, morningness orientation, and prospective memory as measures of mental prospection, and to examine a three-factor model that assumes working memory, mental prospection, and cognitive insight are independent but related higher-order cognitive constructs by using confirmatory factor analysis (CFA). The three-factor model produced a good fit to the data. An alternative one-factor model was tested and rejected. The results suggest that working memory and cognitive insight are distinguishable, related constructs, and that both are distinct from, but negatively associated with, mental prospection. In addition, structural equation modeling (SEM) showed that working memory had a strong positive effect on cognitive insight and a moderate negative effect on mental prospection.

Domain-Specificity of Need for Cognition Among High School Students

2019 ◽  
Vol 35 (5) ◽  
pp. 607-616 ◽  
Author(s):  
Ulrich Keller ◽  
Anja Strobel ◽  
Romain Martin ◽  
Franzis Preckel
Keyword(s):  
High School Students ◽  
Structural Equation ◽  
Factor Model ◽  
Need For Cognition ◽  
Self Concept ◽  
Equation Modeling ◽  
Specific Factor ◽  
General Factor ◽  
Domain Specific ◽  
Specific Factors

Abstract. Need for Cognition (NFC) is increasingly investigated in educational research. In contrast to other noncognitive constructs in this area, such as academic self-concept and interest, NFC has consistently been conceptualized as domain-general. We employed structural equation modeling to address the question of whether NFC can be meaningfully and gainfully conceptualized as domain-specific. To this end, we developed a domain-specific 20-item NFC scale with parallel items for Science, Mathematics, German, and French. Additionally, domain-general NFC was assessed with five domain-general items. Using a cross-sectional sample of more than 4,500 Luxembourgish 9th graders, we found that a nested-factor model incorporating both a general factor and domain-specific factors better accounted for the data than a single-factor or a correlated-factor model. However, the influence of the general factor was markedly stronger than in corresponding models for academic self-concept and interest. When controlling for the domain-specific factors, only Mathematics achievement was significantly predicted by the domain-general factor, while all achievement measures (Mathematics, French, and German) were predicted by the corresponding domain-specific factor. The nested domain-specific NFC factors were clearly empirically distinguishable from first-order domain-specific interest factors.

scholarly journals Factor structure of Raven's Coloured Progressive Matrices

Psico-USF ◽  
2016 ◽  
Vol 21 (2) ◽  
pp. 259-272 ◽  
Author(s):  
Monalisa Muniz ◽  
Cristiano Mauro Assis Gomes ◽  
Sonia Regina Pasian
Keyword(s):  
Standard Deviation ◽  
Factor Structure ◽  
Factor Model ◽  
Specific Factor ◽  
General Factor ◽  
Factor Analyses ◽  
Confirmatory Factor Analyses ◽  
Confirmatory Factor ◽  
Specific Factors ◽  
Three Factor

Abstract This study's objective was to verify the factor structure of Raven's Coloured Progressive Matrices (CPM). The database used included the responses of 1,279 children, 50.2% of which were males with an average age of 8.48 years old and a standard deviation of 1.49 yrs. Confirmatory factor analyses were run to test seven models based on CPM theory and on a Brazilian study addressing the test's structure. The results did not confirm the CPM theoretical proposition concerning the scales but indicated that the test can be interpreted by one general factor and one specific factor or one general factor and three specific factors; both are bi-dimensional models. The three-factor model is, however, more interpretable, suggesting that the factors can be used as a means of screening children's cognitive developmental stage.

Using Exploratory Structural Equation Modeling (ESEM) to Examine the Internal Structure of Posttraumatic Stress Disorder Symptoms

2020 ◽  
Vol 23 ◽  
Author(s):  
Andrés Fresno ◽  
Víctor Arias ◽  
Daniel Núñez ◽  
Rosario Spencer ◽  
Nadia Ramos ◽  
...  
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Structural Equation Modeling ◽  
Posttraumatic Stress ◽  
Factor Structure ◽  
Structural Equation ◽  
Stress Disorder ◽  
Equation Modeling ◽  
General Factor ◽  
Dsm 5 ◽  
Fit Indexes

Abstract Several studies have reported the factor structure of posttraumatic stress disorder (PTSD) using confirmatory factor analysis (CFA). The results show models with different number of factors, high correlations between factors, and symptoms that belong to different factors in different models without affecting the fit index. These elements could suppose the existence of considerable item cross-loading, the overlap of different factors or even the presence of a general factor that explains the items common source of variance. The aim is to provide new evidence regarding the factor structure of PTSD using CFA and exploratory structural equation modeling (ESEM). In a sample of 1,372 undergraduate students, we tested six different models using CFA and two models using ESEM and ESEM bifactor analysis. Trauma event and past-month PTSD symptoms were assessed with Life Events Checklist for DSM-5 (LEC–5) and PTSD Checklist for DSM-5 (PCL–5). All six tested CFA models showed good fit indexes (RMSEA = .051–.056, CFI = .969–.977, TLI = .965–.970), with high correlations between factors (M = .77, SD = .09 to M = .80, SD = .09). The ESEM models showed good fit indexes (RMSEA = .027–.036, CFI = .991–.996, TLI = .985–.992). These models confirmed the presence of cross-loadings on several items as well as loads on a general factor that explained 76.3% of the common variance. The results showed that most of the items do not meet the assumption of dimensional exclusivity, showing the need to expand the analysis strategies to study the symptomatic organization of PTSD.

scholarly journals The Latent-Variable Structure of the Addenbrooke’s Cognitive Examination-Revised

2019 ◽  
Vol 35 (2) ◽  
pp. 205-212 ◽  
Author(s):  
Madeleine L Connolly ◽  
Stephen C Bowden ◽  
Leonie C Simpson ◽  
Malcolm Horne ◽  
Sarah McGregor
Keyword(s):  
Latent Variable ◽  
Structural Equation ◽  
Factor Model ◽  
Five Factor Model ◽  
Variable Structure ◽  
Equation Modeling ◽  
Long Term Memory ◽  
Chc Theory ◽  
Three Factor ◽  
Addenbrooke’S Cognitive Examination

Abstract Objectives To establish a theoretically justified factor structure for the Addenbrooke’s Cognitive Examination-Revised (ACE-R). Methods Our sample comprised 288 patients with Parkinson’s disease (179 men and 109 women). The mean age of participants was 66.66 (SD = 8.93). Confirmatory factor analysis (CFA) was used to evaluate the test developers’ five-factor model of the ACE-R, and alternative models as guided by the Cattell–Horn–Carroll (CHC) theory. Exploratory structural equation modeling (ESEM) was also employed to examine alternative factor structures to ensure that a good candidate model was not overlooked. Results A three-factor CHC-guided CFA and a similar three-factor ESEM model both showed acceptable overall fit, and interpretable factor structures. The three-factor CFA model showed two factors of pure CHC constructs: acquired knowledge (Gc), and visuospatial ability (Gv), and one combined factor, namely, long-term memory retrieval, fluency, and working memory (Glr-Gsm). The three-factor ESEM model showed three factors essentially in line with the CFA results. Conclusion The three-factor CHC-guided CFA model was selected as the best model to guide clinical interpretation of cognitive variables underlying ACE-R scores.

scholarly journals The factor structure of attention-deficit/hyperactivity disorder in schoolchildren

2020 ◽  
Author(s):  
Trine Wigh Arildskov ◽  
Anne Virring ◽  
Rikke Lambek ◽  
Anders Helles Carlsen ◽  
Edmund J.S. Sonuga-Barke ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
General Population ◽  
Factor Structure ◽  
Attention Deficit ◽  
Factor Model ◽  
Clinical Sample ◽  
General Factor ◽  
Hyperactivity Disorder ◽  
Specific Factors ◽  
Three Factor

ABSTRACTThis study investigated the factor structure of attention-deficit/hyperactivity disorder (ADHD) by comparing the fit of a single-factor model, a correlated model with two or three factors, and a bifactor model with one general and two or three specific factors. Different three-factor solutions that varied with regard to the specification of the item “talks excessively” as impulsivity or hyperactivity were also tested. Parent ratings on the ADHD-Rating Scale (ADHD-RS-IV) were collected in a sample of 2044 schoolchildren (1st to 3rd grade) from the general population and in a clinical sample of 165 children and adolescents with ADHD referred to a public regional child and adolescent psychiatric hospital. Confirmatory factor analyses found a satisfactory fit for most models in both samples. However, a correlated three-factor model where “talks excessively” was included as an indicator of impulsivity and especially the bifactor version of this model with one general and three specific factors fit the data slightly better in the general population. In the clinical sample, a number of models performed equally well (the same version of the correlated three-factor model and all the bifactor models). Overall, the factor structure of ADHD seems to be better characterized by a bifactor model with a strong general factor and two or three weaker specific factors. Due to the strong general factor, we suggest emphasizing the ADHD-RS-IV total score rather than the subscale scores in clinical practice.

The dimensions and effects of excessive change

2016 ◽  
Vol 29 (3) ◽  
pp. 445-459 ◽  
Author(s):  
Kevin J. Johnson
Keyword(s):  
Factor Structure ◽  
Structural Equation ◽  
Healthcare Management ◽  
Mediation Effect ◽  
Equation Modeling ◽  
Content Type ◽  
Pilot Sample ◽  
Reactions To Change ◽  
Relationship Of ◽  
Three Factor

Purpose – Change excessiveness is argued as a critical contextual aspect of change management. The purpose of this paper is to identify three major dimensions to change excessiveness: change frequency, extent, and impact. A three-factor structure is proposed to broaden the emerging study on the contextual aspects of change. Its pertinence is proposed in addressing healthcare employees’ exhaustion, change-related uncertainty, and support for change. Design/methodology/approach – Using questionnaires, a first pilot sample (n=131) was recruited to test the psychometric properties and validity of the three-factor structure, while controlling for affectivity. Structural equation modeling techniques following a two-step approach were used on a second sample (n=363). First a confirmatory assessment of the three-factor structure of excessive change is tested. Second, a full mediation effect of excessive change, as a second-order latent factor, regrouping change frequency, impact and extent as first-order factors, was modeled to predict a tripartite conception of change-related reactions: exhaustion, uncertainty, and support for change. Findings – The excessive change three-factor structure is validated, while showing its superiority over alternative models. The fully mediated model is confirmed. Therefore, the significant added effects of change frequency, impact, and extent are positively related to emotional exhaustion and cognitive uncertainty, while negatively related with behavioral support for change. Originality/value – This study contributes by proposing a three-factor structure to excessive change assessment based on previous and independent findings in the literature. It also contributes in modeling the added effect of change frequency, extent, and impact in the full mediation relationship of change excessiveness on a tripartite reactions to change in healthcare management settings.

scholarly journals Toward a Multidimensional Model of Athletes’ Commitment to Coach-Athlete Relationships and Interdependent Sport Teams: A Substantive-Methodological Synergy

2014 ◽  
Vol 36 (1) ◽  
pp. 52-68 ◽  
Author(s):  
Ben Jackson ◽  
Daniel F. Gucciardi ◽  
James A. Dimmock
Keyword(s):  
Bayesian Modeling ◽  
Structural Equation ◽  
Factor Model ◽  
Equation Modeling ◽  
Validity Evidence ◽  
Continuance Commitment ◽  
Sport Teams ◽  
Return Intentions ◽  
Bayesian Structural Equation Modeling ◽  
Three Factor

Drawing from a three-factor model of organizational commitment, we sought to provide validity evidence for a multidimensional conceptualization designed to capture adolescent athletes’ commitment to their coach–athlete relationship or their team. In Study 1, 335 individual-sport athletes (Mage = 17.32, SD = 1.38) completed instruments assessing affective, normative, and continuance commitment to their relationship with their coach, and in Study 2, contextually modified instruments were administered to assess interdependent-sport athletes’ (N = 286, Mage = 16.31, SD = 1.33) commitment to their team. Bayesian structural equation modeling revealed support for a three-factor (in comparison with a single-factor) model, along with relations between commitment dimensions and relevant correlates (e.g., satisfaction, return intentions, cohesion) that were largely consistent with theory. Guided by recent advancements in Bayesian modeling, these studies provide a new commitment instrument with the potential for use and refinement in team- and relationship-based settings and offer preliminary support for a conceptual framework that may help advance our understanding of the factors underpinning individuals’ engagement in sport.

Factor Structure of the Dyadic Adjustment Scale

2019 ◽  
Vol 35 (3) ◽  
pp. 326-334 ◽  
Author(s):  
Dóra Vajda ◽  
Barna Konkolÿ Thege ◽  
Sándor Rózsa
Keyword(s):  
Factor Structure ◽  
Structural Equation ◽  
Dyadic Adjustment ◽  
Equation Modeling ◽  
General Factor ◽  
Dyadic Adjustment Scale ◽  
Confirmatory Factor ◽  
Dyadic Satisfaction ◽  
The Individual ◽  
Relationship Of

Abstract. The Dyadic Adjustment Scale (DAS) is one of the most widely used instruments for measuring relationship quality. Considering the discrepancies across studies regarding the relationship of the underlying constructs of the DAS, the aim of the present study was to examine the factor structure of the scale by applying bifactor models using confirmatory factor analytic (CFA) and exploratory structural equation modeling (ESEM) approaches. The sample consisted of 483 couples recruited in Hungary. The analysis revealed that the bifactor-ESEM yielded the best fit to the data (CFI = .90, RMSEA = .05, WRMR = .88). Further, strict invariance between the sexes was observed for this model. Omega hierarchical coefficients indicated outstanding reliability for the general factor (.86), acceptable estimates for the Dyadic Consensus (.60) and Cohesion (.57) subdomains, but poor reliability for the Dyadic Satisfaction (.22) and Affectional Expression (.36) factors; suggesting that the individual interpretation of these latter two subconstructs must be made with caution.

Exploring the optimal factor structure of the Five Facet Mindfulness Questionnaire: Associations between mindfulness facets and dimensions of psychopathology

2021 ◽  
Author(s):  
Joseph M. Diehl ◽  
Craig Anthony Rodriguez-Seijas ◽  
Justine S. Thompson ◽  
Kristy Dalrymple ◽  
Iwona Chelminski ◽  
...  
Keyword(s):  
Substance Use ◽  
Substance Use Disorders ◽  
Factor Structure ◽  
Structural Equation ◽  
Factor Model ◽  
Equation Modeling ◽  
Clinical Samples ◽  
Underlying Structure ◽  
Five Facet Mindfulness Questionnaire ◽  
Mindfulness Facets

Recent studies of the Five Facet Mindfulness Questionnaire (FFMQ) and its condensed version (FFMQ-SF) fail to replicate the initially proposed 5-factor structure in clinical samples. Failure to adequately understand the dimensionality of common mindfulness measures within clinical samples, therefore, represents an important gap in the current literature. The increasing popularity of mindfulness-based interventions warrants further investigation of differential associations between facets of mindfulness and different forms of psychopathology. We examined (1) the underlying structure of the FFMQ and FFMQ-SF and (2) associations between FFMQ and FFMQ-SF facets and dimensions of psychopathology (i.e. internalizing and substance use disorders) in two large clinical samples (N = 2,779). Results from bass-ackwards analyses suggested similarly defensible 5- and 6-factor models solutions in terms of fit. The 5-factor model was optimal when factoring in parsimony. Exploratory structural equation modeling revealed that all FFMQ facets with the exception of observe were negatively associated with the internalizing factor. Associations with substance use disorders were more complex. In both samples, 5-factor FFMQ and FFMQ-SF models were determined to best represent these data. While deficits in all FFMQ facets with the exception of observe correspond with lower internalizing psychopathology, a more nuanced association was observed with substance use disorders.

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