scholarly journals Searching for G: A New Evaluation of SPM-LS Dimensionality

2019 ◽  
Vol 7 (3) ◽  
pp. 14 ◽  
Author(s):  
Garcia-Garzon ◽  
Abad ◽  
Garrido
Keyword(s):  
Specific Factor ◽  
General Factor ◽  
Graph Analysis ◽  
Reliable Measure ◽  
Initial Validation ◽  
Specific Factors ◽  
Raven's Progressive Matrices ◽  
Essential Unidimensionality ◽  
Future Work ◽  
Short Versions

There has been increased interest in assessing the quality and usefulness of short versions of the Raven’s Progressive Matrices. A recent proposal, composed of the last twelve matrices of the Standard Progressive Matrices (SPM-LS), has been depicted as a valid measure of g. Nonetheless, the results provided in the initial validation questioned the assumption of essential unidimensionality for SPM-LS scores. We tested this hypothesis through two different statistical techniques. Firstly, we applied exploratory graph analysis to assess SPM-LS dimensionality. Secondly, exploratory bi-factor modelling was employed to understand the extent that potential specific factors represent significant sources of variance after a general factor has been considered. Results evidenced that if modelled appropriately, SPM-LS scores are essentially unidimensional, and that constitute a reliable measure of g. However, an additional specific factor was systematically identified for the last six items of the test. The implications of such findings for future work on the SPM-LS are discussed.

How Data Analysis Can Dominate Interpretations of Dominant General Factors

2015 ◽  
Vol 8 (3) ◽  
pp. 438-445 ◽  
Author(s):  
Brenton M. Wiernik ◽  
Michael P. Wilmot ◽  
Jack W. Kostal
Keyword(s):  
Data Analysis ◽  
Substantial Proportion ◽  
Specific Factor ◽  
General Factor ◽  
Data Sets ◽  
Single Factor ◽  
Traditional Methods ◽  
External Variables ◽  
Specific Factors ◽  
Data Analytic

A dominant general factor (DGF) is present when a single factor accounts for the majority of reliable variance across a set of measures (Ree, Carretta, & Teachout, 2015). In the presence of a DGF, dimension scores necessarily reflect a blend of both general and specific factors. For some constructs, specific factors contain little unique reliable variance after controlling for the general factor (Reise, 2012), whereas for others, specific factors contribute a more substantial proportion of variance (e.g., Kinicki, McKee-Ryan, Schriesheim, & Carson, 2002). We agree with Ree et al. that the presence of a DGF has implications for interpreting scores. However, we argue that the conflation of general and specific factor variances has the strongest implications for understanding how constructs relate to external variables. When dimension scales contain substantial general and specific factor variance, traditional methods of data analysis will produce ambiguous or even misleading results. In this commentary, we show how several common data analytic methods, when used with data sets containing a DGF, will substantively alter conclusions.

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.

Comparing Hierarchical Models of Personality Pathology

2018 ◽  
Author(s):  
Whitney R. Ringwald ◽  
Aidan G.C. Wright ◽  
Joseph E. Beeney ◽  
Paul A. Pilkonis
Keyword(s):  
Hierarchical Models ◽  
Empirical Work ◽  
Hierarchical Classification ◽  
Personality Pathology ◽  
General Factor ◽  
Factor Analyses ◽  
Conceptual Structures ◽  
Individual Personality ◽  
Exploratory Factor Analyses ◽  
Specific Factors

Two dimensional, hierarchical classification models of personality pathology have emerged as alternatives to traditional categorical systems: multi-tiered models with increasing numbers of factors and models that distinguish between a general factor of severity and specific factors reflecting style. Using a large sample (N=840) with a range of psychopathology, we conducted exploratory factor analyses of individual personality disorder criteria to evaluate the validity of these conceptual structures. We estimated an oblique, “unfolding” hierarchy and a bifactor model, then examined correlations between these and multi-method functioning measures to enrich interpretation. Four-factor solutions for each model, reflecting rotations of each other, fit well and equivalently. The resulting structures are consistent with previous empirical work and provide support for each theoretical model.

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.

Manifest Anxiety: Unifactorial or Multifactorial Composition?

1965 ◽  
Vol 20 (3) ◽  
pp. 773-780 ◽  
Author(s):  
Walter D. Fenz ◽  
Seymour Epstein
Keyword(s):  
Striated Muscle ◽  
Muscle Tension ◽  
Autonomic Arousal ◽  
Specific Factor ◽  
General Factor ◽  
Personality Variable ◽  
Specific Nature ◽  
Taylor Manifest Anxiety Scale ◽  
Manifest Anxiety ◽  
Differential Contribution

The study investigates three subscales of manifest anxiety, consisting of symptoms of striated muscle tension, symptoms of autonomic arousal, and feelings of fear and insecurity. There was both a general factor of anxiety and a specific factor associated with striated muscle tension. Further evidence for the specific nature of striated muscle tension was indicated by its positive relationship to feelings of hostility, its failure to relate to a personality variable of inhibition, and the relatively high score obtained by males. It was hypothesized that striated muscle tension is more closely associated with overt activity than autonomic symptoms, which represent a deeper level of inhibition. Discrepant results of studies using the Taylor Manifest Anxiety Scale may be due to a failure to take into account the differential contribution of items relating to different kinds of anxiety.

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 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.

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.

scholarly journals Library inventory using a RFID wand: contribution of tag and book specific factors on the read rate

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kasper Abcouwer ◽  
Emiel van Loon
Keyword(s):  
Radio Frequency Identification ◽  
Rfid Tags ◽  
Positive Contribution ◽  
Content Type ◽  
Frequency Identification ◽  
Specific Factors ◽  
Read Rate ◽  
Future Work ◽  
Previous Paragraph ◽  
Practical Implications

PurposeLow read rates are a general problem in library inventories. The purpose of this study is to examine the factors that contribute to the success of library inventory by means of a radio-frequency identification (RFID) inventory taker. The factors investigated were tag position, tag orientation, book thickness, tag density (related to thickness of a sequence of books) and position on the shelf.Design/methodology/approachA total of 210 books were placed in eight random permutations on three fixed book shelves. For each configuration, the RFID tags were read forty times. The resulting data were analysed by means of a generalized linear model, relating the combined contribution of tag position, tag orientation, book thickness and position on the bookshelf to the read rate.FindingsThe tags positioned directly next to the spine were always read, but those near the opening of the book (far from the spine and inventory reader) were not always read. Considering only books with tags near the opening, tag orientation and position on the shelf appeared not to be related to the read rate, while book thickness, thickness over three books and spine tag density appeared to have a small positive contribution to the read rate.Practical implicationsLow read rates during a library inventory can be prevented by placing the tags near the book spine – the other book specific factors (listed in the previous paragraph) are of little influence. When not scanned during a first sweep, repeated scanning can increase the read rate with 0.15.Originality/valueThis paper is one of the first to analyse the influence of tag location and book specific factors on the read rate of RFID tags in library books. The experimental approach sets an example for future work.

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