Comparing score tests and other local dependence diagnostics for the graded response model

Score tests for identifying locally dependent item pairs have been proposed for binary item response models. In this article, both the bifactor and the threshold shift score tests are generalized to the graded response model. For the bifactor test, the generalization is straightforward; it adds one secondary dimension associated only with one pair of items. For the threshold shift test, however, multiple generalizations are possible: in particular, conditional, uniform, and linear shift tests are discussed in this article. Simulation studies show that all of the score tests have accurate Type I error rates given large enough samples, although their small‐sample behaviour is not as good as that of Pearson's Χ² and M₂ as proposed in other studies for the purpose of local dependence (LD) detection. All score tests have the highest power to detect the LD which is consistent with their parametric form, and in this case they are uniformly more powerful than Χ² and M₂; even wrongly specified score tests are more powerful than Χ² and M₂ in most conditions. An example using empirical data is provided for illustration.     

预测视角下双因子模型与高阶因子模型的一般性模拟比较

高阶因子模型本质上是一种特殊的双因子模型, 应用中却常被当做双因子模型的竞争模型。已有研究以满足比例约束的双因子模型(此时等价于一个高阶因子模型)为真实测量模型产生模拟数据, 比较了用双因子模型和高阶因子模型作为测量模型的预测效果。本文使用不满足比例约束的双因子模型(此时不与任何高阶因子模型等价)为真实测量模型产生模拟数据进行比较, 所得结果与满足比例约束的双因子模型的结果有很大差别, 双因子模型结构系数的相对偏差较小、检验力较高, 但第Ⅰ类错误率略高。结论是, 在比例约束条件成立时可以使用高阶因子模型, 否则, 从统计角度看, 一般情况下使用双因子模型进行预测比较好。     

Exploratory Bifactor Analysis: The Schmid-Leiman Orthogonalization and Jennrich-Bentler Analytic Rotations

Analytic bifactor rotations have been recently developed and made generally available, but they are not well understood. The Jennrich-Bentler analytic bifactor rotations (bi-quartimin and bi-geomin) are an alternative to, and arguably an improvement upon, the less technically sophisticated Schmid-Leiman orthogonalization. We review the technical details that underlie the Schmid-Leiman and Jennrich-Bentler bifactor rotations, using simulated data structures to illustrate important features and limitations. For the Schmid-Leiman, we review the problem of inaccurate parameter estimates caused by the linear dependencies, sometimes called “proportionality constraints,” that are required to expand a p correlated factors solution into a (p + 1) (bi)factor space. We also review the complexities involved when the data depart from perfect cluster structure (e.g., item cross-loading on group factors). For the Jennrich-Bentler rotations, we describe problems in parameter estimation caused by departures from perfect cluster structure. In addition, we illustrate the related problems of (a) solutions that are not invariant under different starting values (i.e., local minima problems) and (b) group factors collapsing onto the general factor. Recommendations are made for substantive researchers including examining all local minima and applying multiple exploratory techniques in an effort to identify an accurate model.     

Self‐compassion Is Best Measured as a Global Construct and Is Overlapping with but Distinct from Neuroticism: A Response to Pfattheicher,Geiger, Hartung,Weiss, and Schindler (2017)

Pfattheicher and colleagues recently published an article entitled ‘Old Wine in New Bottles? The Case of Self‐compassion and Neuroticism’ that argues the negative items of the Self‐compassion Scale (SCS), which represent reduced uncompassionate self‐responding, are redundant with neuroticism (especially its depression and anxiety facets) and do not evidence incremental validity in predicting life satisfaction. Using potentially problematic methods to examine the factor structure of the SCS (higher‐order confirmatory factor analysis), they suggest a total self‐compassion score should not be used and negative items should be dropped. In Study 1, we present a reanalysis of their data using what we argue are more theoretically appropriate methods (bifactor exploratory structural equation modelling) that support use of a global self‐compassion factor (explaining 94% of item variance) over separate factors representing compassionate and reduced uncompassionate self‐responding. While self‐compassion evidenced a large correlation with neuroticism and depression and a small correlation with anxiety, it explained meaningful incremental validity in life satisfaction compared with neuroticism, depression, and anxiety. Findings were replicated in Study 2, which examined emotion regulation. Study 3 established the incremental validity of negative items with multiple well‐being outcomes. We conclude that although self‐compassion overlaps with neuroticism, the two constructs are distinct. © 2018 European Association of Personality Psychology     

Bifactor Models of Personality and College Student Performance: A Broad Versus Narrow View

Research in the area of personality traits and academic performance has been supported by consistent meta‐analytic evidence demonstrating positive relationships between Conscientiousness and grade point average (GPA). However, academic performance is not solely a function of GPA but also a number of other important intellectual, interpersonal and intrapersonal behaviours. This wider criterion space opens up the possibility for many personality factors and their underlying facets to relate to academic performance. Using bifactor latent variable modelling, the current study investigates the six‐factor HEXACO model of personality, along with their 24 underlying facets, for predicting students' academic performance. Model results reveal interpretable and meaningful relationships between both broad factors and narrow personality facets in predicting college student outcomes. Implications for measurement, modelling and prediction are discussed. Copyright © 2014 European Association of Personality Psychology     

Complementary variable- and person-centred approaches to the dimensionality of work engagement: a longitudinal investigation

This study illustrates complementary variable- and person-centred approaches to the investigation of the underlying dimensionality of the work engagement construct. A sample of 730 participants completed a questionnaire twice across a four-month period. The results showed that employees’ ratings of their work engagement simultaneously reflected a global overarching work engagement construct, which co-existed with three specific dimensions (vigour, dedication, and absorption). Relying on factor scores from this initial measurement model, the present study examined latent profiles of employees defined based on their global (work engagement) and specific (vigour, dedication, and absorption) levels of work engagement. The results revealed five distinct work engagement profiles, which proved to be fully identical, and highly stable, across the two time points. These profiles characterized disengaged-vigorous, normative, totally disengaged, vigorously absorbed, and engaged yet distanced employees. These profiles were also showed to be meaningfully related to employees’ levels of stress, intentions to leave the organization, health, and job satisfaction.     

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.     

Applying a bifactor model to the functions of relational aggression: Associations with hostile attribution biases and difficulties with emotion regulation

Previous research suggests that reactive and proactive aggression likely have distinct underlying mechanisms that uniquely contribute to the perpetration of each as a result of faulty cognitive and emotional processes. Still, very little work has examined the association of the functions of relational aggression with emotion dysregulation and hostile attribution biases. In addition, it is important to examine relational aggression in its pure and co-occurring functions given that past work finds reactive and proactive aggression to occur both jointly and distinctly. Thus, the current study employed a bifactor model to distinguish between pure reactive, pure proactive, and co-occurring relational aggression in emerging adulthood (N = 647, M_age = 19.92, SD = 2.83), a developmental time period for which relational aggression is particularly prominent. To further address gaps in the relational aggression literature, indirect pathway models revealed that relational hostile attribution biases emerged as a concurrent indirect path in the relationship between emotion dysregulation and pure reactive relational aggression. Furthermore, emotion dysregulation was directly positively associated with both pure functions as well as co-occurring relational aggression, and hostile attribution biases for relational provocations were directly associated with both pure functions of relational aggression, though the association was negative for pure proactive and positive for pure reactive relational aggression. Findings highlight the potential influence of emotion dysregulation and attributing hostile intent to social situations on engaging in the different functions of relational aggression.     

Using bifactor models to identify faking on Big Five questionnaires

To identify faking, bifactor models were applied to Big Five personality data in three studies of laboratory and applicant samples using within‐subjects designs. The models were applied to homogenous data sets from separate honest, instructed faking, applicant conditions, and to simulated applicant data sets containing random individual responses from honest and faking conditions. Factor scores from the general factor in a bifactor model were found to be most highly related to response condition in both types of data sets. Domain factor scores from the faking conditions were found less affected by faking in measurement of Big Five domains than summated scale scores across studies. We conclude that bifactor models are efficacious in assessing the Big Five domains while controlling for faking.     

An item‐level investigation of conceptual and empirical distinctiveness of proactivity constructs

Beyond the prior investigations that took scale‐level approaches to determining discriminant validity in proactivity constructs, the current study contributes a much‐needed interrogation of the items used to measure the behaviors in this domain. The substantive validity (SV) assessments (Study 1) showed that many of the items were judged to be inconsistent with the definition of the construct they assess or, alternatively, more consistent with the definition of a different construct in the domain. Further, exploratory factor analysis revealed the difficulty in empirically separating the four behaviors, while BiM results also advocated against the unique variance of them after accounting for a general factor (Study 2). Altogether, our results show that the items are partly to blame for the empirical redundancy issue.