Riskier Tests of the Validity of the Bifactor Model of Psychopathology

2019 ◽  
Vol 7 (6) ◽  
pp. 1285-1303 ◽  
Author(s):  
Ashley L. Watts ◽  
Holly E. Poore ◽  
Irwin D. Waldman
Keyword(s):  
Community Sample ◽  
General Factor ◽  
Symptom Dimensions ◽  
Bifactor Models ◽  
Specific Factors ◽  
Psychopathology Symptom ◽  
Using Data ◽  
P Factor ◽  
Correlated Factors ◽  
Additional Variance

We advanced several “riskier tests” of the validity of bifactor models of psychopathology, which included that the general and specific psychopathology factors should be reliable and well represented by their respective indicators and that including a general factor should improve on the correlated factor model’s external validity. We compared bifactor and correlated factors models of psychopathology using data from a community sample of youth ( N = 2,498) whose parents provided ratings on psychopathology and theoretically relevant external criteria (i.e., personality, aggression, antisociality). Bifactor models tended to yield either general or specific factors that were unstable and difficult to interpret. The general factor appeared to reflect a differentially weighted amalgam of psychopathology rather than a liability for psychopathology broadly construed. With rare exceptions, bifactor models did not explain additional variance in first-order psychopathology symptom dimensions or external criteria compared with correlated factors models. Together, our findings call into question the validity of bifactor models of psychopathology and the p factor more broadly.

scholarly journals Riskier Tests of the Validity of Bifactor Models of Psychopathology

2019 ◽  
Author(s):  
Ashley L. Watts ◽  
Holly Poore ◽  
Irwin Waldman
Keyword(s):  
Community Sample ◽  
General Factor ◽  
Symptom Dimensions ◽  
Bifactor Models ◽  
Specific Factors ◽  
Psychopathology Symptom ◽  
Using Data ◽  
P Factor ◽  
Correlated Factors ◽  
Additional Variance

We advanced several “riskier tests” of the validity of bifactor models of psychopathology, which included that the general and specific factors should be reliable and well-represented by their indicators, and that including a general factor should improve the correlated factor model’s external validity. We compared bifactor and correlated factors models using data from a community sample of youth (N=2498) whose parents provided ratings on psychopathology and external criteria (i.e., temperament, aggression, antisociality). Bifactor models tended to yield either general or specific factors that were unstable and difficult to interpret. The general factor appeared to reflect a differentially-weighted amalgam of psychopathology rather than a liability for psychopathology broadly construed. With rare exceptions, bifactor models did not explain additional variance in psychopathology symptom dimensions or external criteria compared with correlated factors models. Together, our findings call into question the validity of bifactor models of psychopathology, and the p-factor more broadly.

scholarly journals The p Factor and the n Factor: Associations Between the General Factors of Psychopathology and Neuroticism in Children

2019 ◽  
Author(s):  
Cassandra M Brandes ◽  
Kathrin Herzhoff ◽  
Avante J Smack ◽  
Jennifer L Tackett
Keyword(s):  
Mental Disorders ◽  
Age Groups ◽  
Negative Emotionality ◽  
General Factor ◽  
General Psychopathology ◽  
Bifactor Models ◽  
Specific Factors ◽  
Latent Dimension ◽  
P Factor ◽  
Internalizing And Externalizing

Research across age groups has consistently indicated that psychopathology has a general factor structure, such that there is a broad latent dimension (or p factor) capturing variance common to all mental disorders, as well as specific internalizing and externalizing factors. This research has found that the p factor overlaps substantially with trait negative emotionality (or neuroticism). However, less is known about the psychological substance of the specific factors of the general psychopathology model, or how lower-order facets of neuroticism may relate to each psychopathology factor. We investigated the structure of neuroticism and psychopathology, as well as associations between these domains in a sample of 695 pre-adolescent children using multi-method assessments. We found that both psychopathology and neuroticism may be well-characterized by bifactor models, and that there was substantial overlap between psychopathology (p) and neuroticism (n) general factors, as well as between specific factors (Internalizing with Fear, Externalizing with Irritability).

scholarly journals The p Factor and the n Factor: Associations Between the General Factors of Psychopathology and Neuroticism in Children

2019 ◽  
Vol 7 (6) ◽  
pp. 1266-1284 ◽  
Author(s):  
Cassandra M. Brandes ◽  
Kathrin Herzhoff ◽  
Avanté J. Smack ◽  
Jennifer L. Tackett
Keyword(s):  
Mental Disorders ◽  
Age Groups ◽  
Negative Emotionality ◽  
General Factor ◽  
General Psychopathology ◽  
Bifactor Models ◽  
Specific Factors ◽  
Latent Dimension ◽  
P Factor ◽  
Internalizing And Externalizing

Research across age groups has consistently indicated that psychopathology has a general factor structure such that a broad latent dimension (or p factor) captures variance common to all mental disorders as well as specific internalizing and externalizing factors. This research has found that the p factor overlaps substantially with trait negative emotionality (or neuroticism). However, less is known about the psychological substance of the specific factors of the general psychopathology model or how lower-order facets of neuroticism may relate to each psychopathology factor. We investigated the structure of neuroticism and psychopathology as well as associations between these domains using multimethod assessments in a sample of 695 preadolescent children. We found that both psychopathology and neuroticism may be well characterized by bifactor models and that there was substantial overlap between psychopathology (p) and neuroticism (n) general factors as well as between specific factors (Internalizing with Fear, Externalizing with Irritability).

scholarly journals Going “Up” to Move Forward: S-1 Bifactor Models and the Study of Neurocognitive Abilities in Psychopathology

2021 ◽  
Vol 18 (14) ◽  
pp. 7413
Author(s):  
Darren Haywood ◽  
Frank D. Baughman ◽  
Barbara A. Mullan ◽  
Karen R. Heslop
Keyword(s):  
Structural Models ◽  
General Factor ◽  
Neurocognitive Performance ◽  
Diagnostic Stability ◽  
Psychopathological Symptoms ◽  
Simulation Techniques ◽  
Wide Range ◽  
Bifactor Models ◽  
Specific Factors ◽  
P Factor

Recently, structural models of psychopathology, that address the diagnostic stability and comorbidity issues of the traditional nosological approach, have dominated much of the psychopathology literature. Structural approaches have given rise to the p-factor, which is claimed to reflect an individual’s propensity toward all common psychopathological symptoms. Neurocognitive abilities are argued to be important to the development and maintenance of a wide range of disorders, and have been suggested as an important driver of the p-factor. However, recent evidence argues against p being an interpretable substantive construct, limiting conclusions that can be drawn from associations between p, the specific factors of a psychopathology model, and neurocognitive abilities. Here, we argue for the use of the S-1 bifactor approach, where the general factor is defined by neurocognitive abilities, to explore the association between neurocognitive performance and a wide range of psychopathological symptoms. We use simulation techniques to give examples of how S-1 bifactor models can be used to examine this relationship, and how the results can be interpreted.

scholarly journals Misbegotten Methodologies and Forgotten Lessons from Tom Swift’s Electric Factor Analysis Machine: A Demonstration with Competing Structural Models of Psychopathology

2021 ◽  
Author(s):  
Ashley Lauren Greene ◽  
Ashley L. Watts ◽  
Miriam K. Forbes ◽  
Roman Kotov ◽  
Robert Krueger ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Model Misspecification ◽  
Theory Development ◽  
Structural Models ◽  
General Factor ◽  
Psychological Constructs ◽  
Methodological Choices ◽  
Bifactor Models ◽  
Specific Factors ◽  
P Factor

Confirmatory factor analysis (CFA) and its bifactor models are popular in empirical investigations of the factor structure of psychological constructs. CFA offers straightforward hypothesis testing but has notable pitfalls, such as the imposition of strict assumptions (i.e., simple structure) that obscure unmodeled complexity. Due to the limitations of bifactor CFAs, they have yielded anomalous results across samples and studies that suggest model misspecification (e.g., evaporating specific factors and unexpected loadings). We propose the use of exploratory factor analysis (EFA) to evaluate the structural validity of CFA solutions—either before or after the estimation of more restrictive CFA models—to (1) identify model misspecifications that may drive anomalous estimates and (2) confirm CFA models by examining whether hypothesized structures emerge with limited researcher input. We evaluated the degree to which predominant factor structures were invariant across contexts along the exploratory-confirmatory continuum and demonstrate how poor methodological choices can distort results and impede theory development. All models fit well, but there were numerous differences in replicability and substantive interpretability. Several similarities emerged between bifactor CFA and EFA models, including evidence of overextraction, the collapse of specific factors onto the general factor, and subsequent shifts in how the general factor was defined. We situate these methodological shortcomings within the broader literature on structural models of psychopathology, articulate implications for theories (such as the p-factor) that are borne out of factor analysis, outline several remedies for problems encountered when performing exploratory bifactor analysis, and propose alternative specifications for confirmatory bifactor models.

scholarly journals Strong Homotypic Continuity in Common Psychopathology-, Internalizing-, and Externalizing-Specific Factors Over Time in Adolescents

2016 ◽  
Vol 5 (1) ◽  
pp. 98-110 ◽  
Author(s):  
Hannah R. Snyder ◽  
Jami F. Young ◽  
Benjamin L. Hankin
Keyword(s):  
Community Sample ◽  
Strong Stability ◽  
General Psychopathology ◽  
Bifactor Models ◽  
Specific Factors ◽  
The Stability ◽  
P Factor ◽  
Heterotypic Continuity ◽  
Internalizing And Externalizing ◽  
Over Time

Dimensional models of psychopathology that posit a general psychopathology factor (i.e., p factor), in addition to specific internalizing and externalizing factors, have recently gained prominence. However, the stability of these factors and the specificity with which they are related to one another over time (e.g., homotypic or heterotypic continuity) have not been investigated. The current study addressed these questions. We estimated bifactor models, with p, internalizing-specific, and externalizing-specific factors, with youth and caretaker reports of symptoms at two time points (18 months apart), in a large community sample of adolescents. Results showed strong stability over time with highly specific links (i.e., p factor at Time 1 to Time 2; internalizing-specific at Time 1 to Time 2 and externalizing-specific at Time 1 to Time 2), suggesting strong homotypic continuity between higher order latent psychopathology factors.

scholarly journals Modeling General, Specific, and Method Variance in Personality Measures: Results for ZKA-PQ and NEO-PI-R

Assessment ◽  
2016 ◽  
Vol 25 (8) ◽  
pp. 959-977 ◽  
Author(s):  
Francisco J. Abad ◽  
Miguel A. Sorrel ◽  
Luis Francisco Garcia ◽  
Anton Aluja
Keyword(s):  
Personality Inventory ◽  
Response Styles ◽  
General Factor ◽  
Personality Questionnaire ◽  
Neo Personality Inventory ◽  
Personality Inventories ◽  
Method Factor ◽  
Neo Personality Inventory Revised ◽  
Specific Factors ◽  
Using Data

Contemporary models of personality assume a hierarchical structure in which broader traits contain narrower traits. Individual differences in response styles also constitute a source of score variance. In this study, the bifactor model is applied to separate these sources of variance for personality subscores. The procedure is illustrated using data for two personality inventories—NEO Personality Inventory–Revised and Zuckerman–Kuhlman–Aluja Personality Questionnaire. The inclusion of the acquiescence method factor generally improved the fit to acceptable levels for the Zuckerman–Kuhlman–Aluja Personality Questionnaire, but not for the NEO Personality Inventory–Revised. This effect was higher in subscales where the number of direct and reverse items is not balanced. Loadings on the specific factors were usually smaller than the loadings on the general factor. In some cases, part of the variance was due to domains being different from the main one. This information is of particular interest to researchers as they can identify which subscale scores have more potential to increase predictive validity.

scholarly journals The P Factor in Children: Relationships with Executive Functions and Effortful Control

2021 ◽  
Author(s):  
Allison Shields ◽  
Kathleen Wade Reardon ◽  
Cassandra M Brandes ◽  
Jennifer L Tackett
Keyword(s):  
Executive Functions ◽  
Effortful Control ◽  
Community Sample ◽  
Self Regulation ◽  
Psychological Disorders ◽  
General Psychopathology ◽  
Large N ◽  
P Factor ◽  
Regulatory Functions ◽  
Correlated Factors

Lower levels of self-regulation have been implicated in multiple psychological disorders. Despite conceptual overlap (broadly reflecting self-regulatory functions), executive functions (EF) and effortful control (EC) are rarely jointly studied in relation to broadband psychopathology. The present study investigated associations of correlated factors (internalizing-externalizing) and bifactor psychopathology models with EF and EC in a large (N=895) childhood community sample (Mage = 11.54, SDage = 2.25). Associations between both self-regulation constructs (EF and EC) with psychopathology were largely accounted for via a general psychopathology factor. However, EC evidenced stronger associations, questioning the utility of task-based EF measures to inform self-regulatory psychopathology.

Generality or Specificity? Examining the Relation between Personality Traits and Mental Health Outcomes Using a Bivariate Bi–factor Latent Change Model

2016 ◽  
Vol 30 (5) ◽  
pp. 467-483 ◽  
Author(s):  
Wenting Mu ◽  
Jing Luo ◽  
Lauren Nickel ◽  
Brent W. Roberts
Keyword(s):  
Mental Health ◽  
Personality Traits ◽  
Panel Study ◽  
General Factor ◽  
Latent Factors ◽  
Personality Psychology ◽  
Change Models ◽  
Pairwise Correlations ◽  
Specific Factors ◽  
Using Data

Most previous research has focused on the relationships between specific personality traits and specific facets of mental health. However, in reality most of the Big Five are associated at non–trivial levels with mental health. To account for this broad correlation, we proposed the ‘barometer hypothesis’, positing that behind both ratings of mental health and personality lies a barometer that indicates one's general feelings of positivity or negativity. To the extent that both the general factors of personality and mental health reflect this same barometer, we would expect them to be correlated. We tested alternative models using data from a large longitudinal panel study that includes two cohorts of participants who were assessed every two years, resulting in parallel 4–year longitudinal studies. Similar results were obtained across both studies. Supporting the ‘barometer hypothesis’, findings revealed that the optimal model included general latent factors for both personality traits and mental health. Compared to the broad raw pairwise correlations, the bi–factor latent change models revealed that the relation among levels and changes in the specific factors were substantially reduced when controlling for the general factors. Still, some relations remained relatively unaffected by the inclusion of the general factor. We discuss implications of these findings. Copyright © 2016 European Association of Personality Psychology

Issues in Estimating Interpretable Lower Order Factors in Second-Order Hierarchical Models: Commentary on Clark et al. (2021)

2021 ◽  
pp. 216770262110351
Author(s):  
Tyler M. Moore ◽  
Benjamin B. Lahey
Keyword(s):  
Lower Order ◽  
Hierarchical Modeling ◽  
Simulated Data ◽  
Second Order ◽  
General Factor ◽  
Bifactor Models ◽  
Specific Factors ◽  
Factor Modeling ◽  
Highly Correlated ◽  
Criterion Variables

In a previous issue of Clinical Psychological Science, Clark and colleagues asserted that lower order factors in second-order models are comparable with specific factors in bifactor models when residualized on the general factor. Modeling simulated data demonstrated that residualized lower order factors are correlated with bifactor-specific factors only to the extent that factor loadings are proportional. Modeling actual data with violations of proportionality showed that specific and residualized lower order factors are not always highly correlated and have differential correlations with criterion variables even when both models fit acceptably. Because proportionality constraints limit only second-order models, bifactor models should be the first option for hierarchical modeling.

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