Bifactor Modeling Approach Research Articles

Measuring errors and violations on the road: A bifactor modeling approach to the Driver Behavior Questionnaire

The Driver Behavior Questionnaire (DBQ) is a self-report measure of driving behavior that has been widely used over more than 20 years. Despite this wealth of evidence a number of questions remain, including understanding the correlation between its violations and errors sub-components, identifying how these components are related to crash involvement, and testing whether a DBQ based on a reduced number of items can be effective. We address these issues using a bifactor modeling approach to data drawn from the UK Cohort II longitudinal study of novice drivers. This dataset provides observations on 12,012 drivers with DBQ data collected at .5, 1, 2 and 3 years after passing their test. A bifactor model, including a general factor onto which all items loaded, and specific factors for ordinary violations, aggressive violations, slips and errors fitted the data better than correlated factors and second-order factor structures. A model based on only 12 items replicated this structure and produced factor scores that were highly correlated with the full model. The ordinary violations and general factor were significant independent predictors of crash involvement at 6 months after starting independent driving. The discussion considers the role of the general and specific factors in crash involvement.

A bifactor approach to modelling the Rosenberg Self Esteem Scale

Inconsistency exists in the empirical literature with respect to the underlying factor structure of the Rosenberg Self-Esteem Scale (RSES; Rosenberg, 1989). In research contexts the RSES is considered a unidimensional measure of self-esteem. Empirical findings have undermined this conceptualisation with factor analytic findings favouring a variety of one-factor solutions (with correlated measurement errors) or multidimensional representations. The current study applied a bifactor modelling approach to provide a theoretical and methodologically satisfying resolution to the current inconsistency. Three alternative factor models of the RSES were tested among a large sample of the adult population (N=6082). Results indicated that a bifactor model was the best fit of the data. This model was demonstrated to be factorially invariant among males and females. The reliability of the scale was established using composite reliability. Results are discussed in terms of resolving the debate about the appropriate factor structure of the RSES.

Unique self-leadership: A bifactor model approach

A crucial point of debate around the construct of self-leadership is its supposed lack of distinctiveness from other theoretically related constructs. We empirically investigate in professionals with leadership experience ( N = 374) with a bifactor structural equation modeling approach to what extent self-leadership (a) is distinct from related classic motivation constructs (need for achievement, self-regulation, self-efficacy) and (b) harbors incremental predictive validity over and above these motivation constructs in predicting individual job performance and leadership behavior styles (transformational leadership, transactional leadership, laissez-faire leadership). Findings yielded that self-leadership (a) generally showed only moderate associations with constructs of classic motivation literature and was sufficiently distinct from them and (b) could incrementally predict outcomes above and beyond related classic motivation constructs, alluding to its uniqueness. We discuss self-leadership as a unique and useful construct worthy of own systematic research.

Bifactor Modeling and the Estimation of Model-Based Reliability in the WAIS-IV

Previous confirmatory factor analytic research that has examined the factor structure of the Wechsler Adult Intelligence Scale–Fourth Edition (WAIS-IV) has endorsed either higher order models or oblique factor models that tend to amalgamate both general factor and index factor sources of systematic variance. An alternative model that has not yet been examined for the WAIS-IV is the bifactor model. Bifactor models allow all subtests to load onto both the general factor and their respective index factor directly. Bifactor models are also particularly amenable to the estimation of model-based reliabilities for both global composite scores (ω h ) and subscale/index scores (ω s ). Based on the WAIS-IV normative sample correlation matrices, a bifactor model that did not include any index factor cross loadings or correlated residuals was found to be better fitting than the conventional higher order and oblique factor models. Although the ω h estimate associated with the full scale intelligence quotient (FSIQ) scores was respectably high (.86), the ω s estimates associated with the WAIS-IV index scores were very low (.13 to .47). The results are interpreted in the context of the benefits of a bifactor modeling approach. Additionally, in light of the very low levels of unique internal consistency reliabilities associated with the index scores, it is contended that clinical index score interpretations are probably not justifiable.

Modeling the Structure of the Attitudes and Belief Scale 2 using CFA and Bifactor Approaches: Toward the Development of an Abbreviated Version

The Attitudes and Belief Scale-2 (ABS-2: DiGiuseppe, Leaf, Exner, & Robin, 1988. The development of a measure of rational/irrational thinking. Paper presented at the World Congress of Behavior Therapy, Edinburg, Scotland.) is a 72-item self-report measure of evaluative rational and irrational beliefs widely used in Rational Emotive Behavior Therapy research contexts. However, little psychometric evidence exists regarding the measure's underlying factor structure. Furthermore, given the length of the ABS-2 there is a need for an abbreviated version that can be administered when there are time demands on the researcher, such as in clinical settings. This study sought to examine a series of theoretical models hypothesized to represent the latent structure of the ABS-2 within an alternative models framework using traditional confirmatory factor analysis as well as utilizing a bifactor modeling approach. Furthermore, this study also sought to develop a psychometrically sound abbreviated version of the ABS-2. Three hundred and thirteen (N = 313) active emergency service personnel completed the ABS-2. Results indicated that for each model, the application of bifactor modeling procedures improved model fit statistics, and a novel eight-factor intercorrelated solution was identified as the best fitting model of the ABS-2. However, the observed fit indices failed to satisfy commonly accepted standards. A 24-item abbreviated version was thus constructed and an intercorrelated eight-factor solution yielded satisfactory model fit statistics. Current results support the use of a bifactor modeling approach to determining the factor structure of the ABS-2. Furthermore, results provide empirical support for the psychometric properties of the newly developed abbreviated version.

Is Relational Aggression Part of the Externalizing Spectrum? A Bifactor Model of Youth Antisocial Behavior

The primary purpose of the present study was to examine support for the inclusion of relational aggression (RAgg) alongside physical aggression (Agg) and rule-breaking behaviors (RB) as a subfactor of antisocial behavior (ASB). Caregiver reports were collected for 1,087 youth (48.9% male) ages 6-18. Results indicated that all three subfactors of ASB demonstrated substantial loadings on a general ASB factor. Using a bifactor model approach, specific factors representing each ASB subfactor were simultaneously modeled, allowing for examination of common and specific correlates. At the scale level, results demonstrated consistently strong connections with high Neuroticism and low Agreeableness across all 3 ASB subfactors, a pattern which was replicated for the general ASB factor in the bifactor approach. Specific factors in the bifactor model demonstrated connections with personality and psychopathology correlates, primarily for Agg. These findings provide some support for an overall grouping of RAgg with other ASB subfactors in youth, and further distinguish Agg as potentially representing a more potent variant of youth ASB relative to both RB and RAgg.

Developmental differences in structure of attention-deficit/hyperactivity disorder (ADHD) between childhood and adulthood

The current paper utilizes a bifactor modeling approach to evaluate the structure of attention-deficit/hyperactivity disorder (ADHD) in adulthood and assess developmental continuity of ADHD structure between childhood and adulthood. The study compared traditional one-factor, two-factor, three-factor, and second-order factor models of ADHD with a bifactor model of ADHD. Developmental differences in ADHD structure were examined using an extension of the bifactor model: a two-group model comparing children and adults. Participants were 406 adults (49% male; 145 of 406 with ADHD), (18 to 37) years old, and 548 children (58% male; 302 of 548 with ADHD), 6 to 18 years old. A bifactor model of ADHD exhibited the best fit in adults and children compared to traditional models, suggesting continuity in the ADHD latent construct across development. However, significant differences in the factor loadings were evident between children and adults in the two-group bifactor model, suggesting changes in the relative importance of particular symptoms over time. Namely, hyperactivity symptoms appear to decline in importance relative to the ADHD phenotype between childhood and adulthood.

General and specific components of depression and anxiety in an adolescent population

BackgroundDepressive and anxiety symptoms often co-occur resulting in a debate about common and distinct features of depression and anxiety.MethodsAn exploratory factor analysis (EFA) and a bifactor modelling approach were used to separate a general distress continuum from more specific sub-domains of depression and anxiety in an adolescent community sample (n = 1159, age 14). The Mood and Feelings Questionnaire and the Revised Children's Manifest Anxiety Scale were used.ResultsA three-factor confirmatory factor analysis is reported which identified a) mood and social-cognitive symptoms of depression, b) worrying symptoms, and c) somatic and information-processing symptoms as distinct yet closely related constructs. Subsequent bifactor modelling supported a general distress factor which accounted for the communality of the depression and anxiety items. Specific factors for hopelessness-suicidal thoughts and restlessness-fatigue indicated distinct psychopathological constructs which account for unique information over and above the general distress factor. The general distress factor and the hopelessness-suicidal factor were more severe in females but the restlessness-fatigue factor worse in males. Measurement precision of the general distress factor was higher and spanned a wider range of the population than any of the three first-order factors.ConclusionsThe general distress factor provides the most reliable target for epidemiological analysis but specific factors may help to refine valid phenotype dimensions for aetiological research and assist in prognostic modelling of future psychiatric episodes.