Don’t Use a Bifactor Model Unless You Believe the True Structure Is Bifactor

2020 ◽  
pp. 073428292097771
Author(s):  
Scott L. Decker
Keyword(s):  
Statistical Methods ◽  
Clinical Applications ◽  
Bifactor Model ◽  
General Factor ◽  
Cognitive Tests ◽  
Theoretical Justification ◽  
Current Article ◽  
True Structure ◽  
Cognitive Dimensions

The current article provides a response to concerns raised by Dombrowski, McGill, Canivez, Watkins, & Beaujean (2020) regarding the methodological confounds identified by Decker, Bridges, Luedke, and Eason (2020) for using a bifactor (BF) model and Schmid–Leiman (SL) procedure in previous studies supporting a general factor of intelligence (i.e., “g”). While Dombrowski et al. (2020) raised important theoretical and practical issues, the theoretical justification for using a BF model and SL procedure to identify cognitive dimensions remain unaddressed, as well as significant concerns for using these statistical methods as the basis for informing the use of cognitive tests in clinical applications.

The Relationship Between Career Adaptability and Job-Search Self-Efficacy of Graduates: The Bifactor Approach

2021 ◽  
pp. 106907272110022
Author(s):  
Marijana Matijaš ◽  
Darja Maslić Seršić
Keyword(s):  
Job Search ◽  
Self Efficacy ◽  
Cross Sectional Study ◽  
Sem Analysis ◽  
Bifactor Model ◽  
Specific Factor ◽  
General Factor ◽  
Career Adaptability ◽  
Cross Sectional ◽  
Interview Performance

Career adaptability is an important resource for dealing with career transitions such as the transition from university to work. Previous research emphasized the importance of focusing on career adapt-abilities instead only on general career adaptability. The aim of this research was to investigate whether career adaptability can be conceptualized as a bifactor model and whether general and specific dimensions of career adaptability have a relationship with job-search self-efficacy of graduates. In an online cross-sectional study, 667 graduates completed the Career Adapt-Abilities Scale and Job Search Skill and Confidence Scale. The CFA analysis showed that the bifactor model of career adaptability had a good fit where general factor explained most of the items’ variance. The SEM analysis revealed that general career adaptability and the specific factor of confidence positively correlated with job-search and interview performance self-efficacy. Control only correlated with interview performance self-efficacy. Neither concern nor curiosity showed a significant relationship with job-search and interview performance self-efficacy.

The Test of Gross Motor Development—Third Edition: A Bifactor Model, Dimensionality, and Measurement Invariance

2021 ◽  
pp. 1-16
Author(s):  
Sedigheh Salami ◽  
Paulo Felipe Ribeiro Bandeira ◽  
Cristiano Mauro Assis Gomes ◽  
Parvaneh Shamsipour Dehkordi
Keyword(s):  
Measurement Invariance ◽  
Motor Development ◽  
Goodness Of Fit ◽  
Factor Model ◽  
Bifactor Model ◽  
General Factor ◽  
Convenience Sample ◽  
Gross Motor ◽  
Measurement Models ◽  
Gross Motor Development

Aim: To examine the latent structure of the Test of Gross Motor Development—Third Edition (TGMD-3) with a bifactor modeling approach. In addition, the study examines the dimensionality and model-based reliability of general and specific contributions of the test’s subscales and measurement invariance of the TGMD-3. Methods: A convenience sample of (N = 496; Mage = 7.23 ± 2.03 years; 53.8% female) typically developed children participated in this study. Three alternative measurement models were tested: (a) a unidimensional model, (b) a correlated two-factor model, and (c) a bifactor model. Results: The totality of results, including item loadings, goodness-of-fit indexes, and reliability estimates, all supported the bifactor model and strong evidence of a general factor, namely gross motor competence. Additionally, the reliability of subscale scores was poor, and it is thus contended that scoring, reporting, and interpreting of the subscales scores are probably not justifiable. Conclusions: This study shows the advantages of using bifactor approach to examine the TGMD-3 factor structure and suggests that the two traditionally hypothesized factors are better understood as “grouping” factors rather than as representative of latent constructs. In addition, our findings demonstrate that the bifactor model appears invariant for sex.

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

scholarly journals Estimating feedforward and feedback effective connections from fMRI time series: Assessments of statistical methods

2019 ◽  
Vol 3 (2) ◽  
pp. 274-306 ◽  
Author(s):  
Ruben Sanchez-Romero ◽  
Joseph D. Ramsey ◽  
Kun Zhang ◽  
Madelyn R. K. Glymour ◽  
Biwei Huang ◽  
...  
Keyword(s):  
Time Series ◽  
Statistical Methods ◽  
Permutation Test ◽  
Causal Structure ◽  
Multiple Model ◽  
New Methods ◽  
Test Models ◽  
Non Gaussian ◽  
True Structure ◽  
Better Than

We test the adequacies of several proposed and two new statistical methods for recovering the causal structure of systems with feedback from synthetic BOLD time series. We compare an adaptation of the first correct method for recovering cyclic linear systems; Granger causal regression; a multivariate autoregressive model with a permutation test; the Group Iterative Multiple Model Estimation (GIMME) algorithm; the Ramsey et al. non-Gaussian methods; two non-Gaussian methods by Hyvärinen and Smith; a method due to Patel et al.; and the GlobalMIT algorithm. We introduce and also compare two new methods, Fast Adjacency Skewness (FASK) and Two-Step, both of which exploit non-Gaussian features of the BOLD signal. We give theoretical justifications for the latter two algorithms. Our test models include feedback structures with and without direct feedback (2-cycles), excitatory and inhibitory feedback, models using experimentally determined structural connectivities of macaques, and empirical human resting-state and task data. We find that averaged over all of our simulations, including those with 2-cycles, several of these methods have a better than 80% orientation precision (i.e., the probability of a directed edge is in the true structure given that a procedure estimates it to be so) and the two new methods also have better than 80% recall (probability of recovering an orientation in the true structure).

Psychometric properties of a new scale for measuring academic positive psychological capital

2021 ◽  
pp. 25-30
Author(s):  
Pasquale Anselmi ◽  
Daiana Colledani ◽  
Luigi Fabbris ◽  
Egidio Robusto ◽  
Manuela Scioni
Keyword(s):  
Psychological Capital ◽  
Factor Model ◽  
Bifactor Model ◽  
Specific Factor ◽  
General Factor ◽  
Positive Psychological Capital ◽  
Four Dimensions ◽  
Explained Common Variance ◽  
University Of Padua ◽  
Academic Results

Positive psychological capital (PsyCap) is the name given to a set of psychological dimensions (hope, resilience, self-efficacy, and optimism) that may support students in their effort to achieve better academic results and even improve the employability of graduates. These dimensions could help students to achieve better academic results and impact fresh graduates’ ability to stand the labour market in times of crisis. A scale, called Academic PsyCap, was specifically developed to evaluate the four PsyCap dimensions among students and fresh graduates. To deeply investigate the structural validity of the scale, three alternative models (one-factor model, correlated four-factor model, bifactor model) were run on the responses provided by about 1,600 fresh graduates at the University of Padua. The results indicated that the bifactor model fit the data better than the other two models. In this model, all items significantly loaded on both their own domain specific factor and on the general factor. The values of Percentage of Uncontaminated Correlations (PUC), Explained Common Variance (ECV), and Hierarchical Omega suggested that multidimensionality in the scale was not severe enough to disqualify the use of a total PsyCap score. The scale was found to be invariant across gender and academic degree (bachelor’s and master’s degree). Internal consistency indices were satisfactory for the four dimensions and the total scale.

Structural Validity and Reliability of Social, Academic, and Emotional Behavior Risk Screener–Student Rating Scale Scores: A Replication Study

2020 ◽  
pp. 153450842090952 ◽  
Author(s):  
Stephen P. Kilgus ◽  
Katie Eklund ◽  
Nathaniel P. von der Embse ◽  
Madison Weist ◽  
Alexandra J. Barber ◽  
...  
Keyword(s):  
Social Behavior ◽  
Internal Consistency ◽  
Rating Scale ◽  
Bifactor Model ◽  
Emotional Behavior ◽  
Student Rating ◽  
General Factor ◽  
Structural Validity ◽  
Acceptable Internal Consistency ◽  
Total Behavior

The purpose of this study was to evaluate the structural validity, internal consistency, and measurement invariance of scores from the Social, Academic, and Emotional Behavior Risk Screener–Student Rating Scale (mySAEBRS), a student self-report universal screening tool. Participants included 24,094 K–12 students who completed the mySAEBRS. Confirmatory factor analyses (CFAs) supported the fit of a bifactor model, wherein each item corresponding to both a general factor (i.e., Total Behavior) and one of three narrow factors (i.e., Social Behavior, Academic Behavior, and Emotional Behavior). Such model fit was superior to that of alternative factor structures (i.e., unidimensional, correlated-factor, and higher order). A review of pattern coefficients suggested items were relatively split, with some items loading higher on the general factor and others loading higher on their narrow factor. A series of multigroup CFAs supported the configural and metric invariance of the bifactor model, while yielding less consistent support for scalar/threshold invariance. Omega reliability coefficients indicated each mySAEBRS scale was associated with acceptable internal consistency (>.70). However, when accounting for other factors, only the Total Behavior, Social Behavior, and Emotional Behavior scales demonstrated acceptable internal consistency (i.e., >.50). Implications for practice and directions for future research are discussed.

scholarly journals Negative Problems Orientation Questionnaire for Chinese Adolescents: Bifactor Model and Measurement Invariance

2020 ◽  
Vol 11 ◽  
Author(s):  
Huiwen Xiao ◽  
Rongmao Lin ◽  
Qiaoling Wu ◽  
Saili Shen ◽  
Youwei Yan
Keyword(s):  
Measurement Invariance ◽  
Bifactor Model ◽  
Chinese Adolescents ◽  
General Factor ◽  
Problem Orientation ◽  
Domain Specific ◽  
Multiple Group ◽  
Gender And Age ◽  
Specific Factors ◽  
Negative Problem Orientation

The Negative Problem Orientation Questionnaire (NPOQ) is a widely used tool for assessing negative problem orientation (NPO). However, its construct and measurement invariance has not been adequately tested in adolescents. The present study explored the possible construct of the NPOQ and its measurement invariance in a sample of 754 Chinese adolescents (51.6% girls, all 12–18 years old). The results supported a bifactor model of the NPOQ that consists of a general factor NPO and three domain-specific factors including perceived threat, self-inefficacy, and negative outcome expectancy. A multiple-group CFA indicated that the bifactor model showed strict invariance across gender and age. The general and domain factors showed unique variance in indexes of worry, depression, anxiety, and stress, which supported well incremental validity of them. This study confirms for a bifactor conceptualization of the NPOQ and its measurement invariance across gender and age in Chinese adolescents. Additionally, it is recommended that the total score should be used to assess NPO in Chinese adolescents.

I've Found It, but What Does It Mean? On the Importance of Theory in Identifying Dominant General Factors

2016 ◽  
Vol 9 (1) ◽  
pp. 212-216 ◽  
Author(s):  
Zhenyu Yuan
Keyword(s):  
Job Performance ◽  
Statistical Properties ◽  
Performance Ratings ◽  
General Factor ◽  
Important Criterion ◽  
Theoretical Justification ◽  
Definition Of

In their focal article, Ree, Carretta, and Teachout (2015) based their definition of a dominant general factor (DGF) on two criteria: (a) A DGF should be the largest source of reliable variance; (b) it is influencing every variable measuring the construct. Although detailed attention has been paid to the statistical properties of a DGF, I believe another criterion of equal if not greater importance is the theoretical justification to expect a DGF in the measurement of a construct. In the following commentary, I will highlight the importance of theory as another important criterion when determining the meaningfulness and usefulness of DGFs, discuss the risks of creating a DGF without any theoretical guidance, and elaborate on the complexities surrounding job performance as a detailed example to illustrate why theory is important before extracting a DGF from performance ratings.

Higher-Order and Bifactor Models of the Drinking Motives Questionnaire

Assessment ◽  
2016 ◽  
Vol 24 (2) ◽  
pp. 222-231 ◽  
Author(s):  
Andrew Lac ◽  
Candice D. Donaldson
Keyword(s):  
Structural Equation ◽  
Negative Reinforcement ◽  
Factor Model ◽  
Equation Model ◽  
Higher Order ◽  
Bifactor Model ◽  
Drinking Motives ◽  
General Factor ◽  
Fit Indices ◽  
Confirmatory Factor Analyses

The Drinking Motives Questionnaire, previously postulated and documented to exhibit a measurement structure of four correlated factors (social, enhancement, conformity, and coping), is a widely administered assessment of reasons for consuming alcohol. In the current study ( N = 552), confirmatory factor analyses tested the plausibility of several theoretically relevant factor structures. Fit indices corroborated the original four-factor model, and also supported a higher-order factor model involving a superordinate motives factor that explicated four subordinate factors. A bifactor model that permitted items to double load on valence type (positive or negative reinforcement) and source type (external or internal) generated mixed results, suggesting that this 2 × 2 motivation paradigm was not entirely tenable. Optimal fit was obtained for a bifactor model depicting a general factor and four specific factors of motives. Latent factors derived from this structure exhibited criterion validity in predicting frequency and quantity of alcohol usage in a structural equation model. Findings are interpreted in the context of theoretical implications of the instrument, alternative factor structures of drinking motives, and assessment applications.

scholarly journals A Bifactor Model of Subjective Well-Being at Personal, Community, and Country Levels: A Case With Three Latin-American Countries

2021 ◽  
Vol 12 ◽  
Author(s):  
Javier Torres-Vallejos ◽  
Joel Juarros-Basterretxea ◽  
Juan Carlos Oyanedel ◽  
Masatoshi Sato
Keyword(s):  
Latin American ◽  
Well Being ◽  
Bifactor Model ◽  
General Factor ◽  
Subjective Well Being ◽  
Specific Level ◽  
Single Measure ◽  
Individual Level ◽  
The Individual ◽  
Latin American Countries

Improving citizens' subjective well-being (SWB) has become an increasingly visible policy goal across industrialized countries. Although an increasing number of studies have investigated SWB at the individual level, little is known about subjective evaluation at social levels, such as the community and national levels. While the relationships between these levels have been analyzed in previous research, these assessments, which are part of the same unique construct of SWB, are under-investigated. The purpose of this study was to examine the dimensionality and reliability of a single measure of SWB, which contained individual, community, and national levels across three Latin-American countries (Argentina, Chile, and Venezuela), using a bifactor model analysis. Findings showed that the bifactor model exhibited a good fit to the data for the three countries. However, invariance testing between countries was not fully supported because of each item's specific contribution to both specific and general constructs. The analyses of each country showed that the SWB construct was in a gray area between unidimensionality and multidimensionality; some factors contributed more to the general factor and others to the specific level, depending on the country. These findings call for integrating more distant levels (community and country levels) into the understanding of SWB at the individual level, as they contribute not only to an overall construct, but they make unique contributions to SWB, which must be considered in public policy making.

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